v1.7.1

Overview

• Fix Vulkan crashes
• Performance stats for Vulkan on RTX 2060

GPU	Config	Model	Th	FA	Enc.	Dec.	Bch5	PP	Commit
RTX 2060	VULKAN	tiny	1	0	30.38	1.37	1.04	0.05	9f346d0
RTX 2060	VULKAN	tiny-q5_0	1	0	20.98	1.38	0.99	0.05	9f346d0
RTX 2060	VULKAN	tiny-q5_1	1	0	20.74	1.30	0.96	0.05	9f346d0
RTX 2060	VULKAN	base	1	0	44.69	1.59	1.78	0.09	9f346d0
RTX 2060	VULKAN	base-q5_0	1	0	39.72	2.11	1.72	0.08	9f346d0
RTX 2060	VULKAN	base-q5_1	1	0	39.45	2.01	1.63	0.08	9f346d0
RTX 2060	VULKAN	small	1	0	160.02	3.53	4.64	0.23	9f346d0
RTX 2060	VULKAN	small-q5_0	1	0	141.52	4.54	4.44	0.20	9f346d0
RTX 2060	VULKAN	small-q5_1	1	0	141.03	4.63	4.18	0.20	9f346d0
RTX 2060	VULKAN	medium	1	0	472.66	7.55	11.35	0.56	9f346d0
RTX 2060	VULKAN	medium-q5_0	1	0	395.55	9.81	10.64	0.49	9f346d0
RTX 2060	VULKAN	medium-q5_1	1	0	398.85	10.16	10.15	0.50	9f346d0
RTX 2060	VULKAN	medium-dis	1	0	427.26	1.26	1.20	0.08	9f346d0
RTX 2060	VULKAN	large-v2	1	0	924.60	12.36	18.56	1.01	9f346d0
RTX 2060	VULKAN	large-v2-q5_0	1	0	774.21	17.25	17.17	0.85	9f346d0
RTX 2060	VULKAN	large-v2-q5_1	1	0	779.75	17.44	16.27	0.85	9f346d0
RTX 2060	VULKAN	large-v2-dis	1	0	833.35	1.38	1.56	0.10	9f346d0
RTX 2060	VULKAN	large-v3-turbo	1	0	839.90	2.11	2.70	0.16	9f346d0
RTX 2060	VULKAN	large-v3-turbo-q5_0	1	0	705.49	3.22	2.53	0.14	9f346d0

What's Changed

• Retry allocation with fallback flags by @SRHMorris in #2451

New Contributors

• @SRHMorris made their first contribution in #2451

Full Changelog: v1.7.0...v1.7.1

v1.7.0

Overview

• Fix crashes with high number of beams
• Reduce overal VRAM usage
• Optimize Encoder performance

Some performance numbers for this release:

M2 Ultra

Flash Attention ON:

GPU	Config	Model	Th	FA	Enc.	Dec.	Bch5	PP	Commit
M2 Ultra	METAL	tiny	1	1	8.37	1.44	0.48	0.01	6a94163
M2 Ultra	METAL	tiny-q5_0	1	1	9.81	1.46	0.50	0.01	6a94163
M2 Ultra	METAL	tiny-q5_1	1	1	8.80	1.47	0.50	0.01	6a94163
M2 Ultra	METAL	base	1	1	16.11	1.96	0.74	0.02	6a94163
M2 Ultra	METAL	base-q5_0	1	1	16.38	1.99	0.78	0.02	6a94163
M2 Ultra	METAL	base-q5_1	1	1	16.72	2.00	0.77	0.02	6a94163
M2 Ultra	METAL	small	1	1	41.26	3.88	1.66	0.05	6a94163
M2 Ultra	METAL	small-q5_0	1	1	46.91	4.02	1.76	0.06	6a94163
M2 Ultra	METAL	small-q5_1	1	1	47.05	4.00	1.73	0.06	6a94163
M2 Ultra	METAL	medium	1	1	111.29	7.79	3.63	0.11	6a94163
M2 Ultra	METAL	medium-q5_0	1	1	129.78	7.71	3.85	0.13	6a94163
M2 Ultra	METAL	medium-q5_1	1	1	129.29	7.71	3.87	0.13	6a94163
M2 Ultra	METAL	medium-dis	1	1	99.27	1.09	0.43	0.02	6a94163
M2 Ultra	METAL	large-v2	1	1	198.81	11.54	5.59	0.20	6a94163
M2 Ultra	METAL	large-v2-q5_0	1	1	236.18	11.12	6.11	0.24	6a94163
M2 Ultra	METAL	large-v2-q5_1	1	1	235.88	11.14	6.01	0.24	6a94163
M2 Ultra	METAL	large-v2-dis	1	1	177.41	1.21	0.48	0.02	6a94163
M2 Ultra	METAL	large-v3-turbo	1	1	178.92	1.89	0.83	0.03	6a94163
M2 Ultra	METAL	large-v3-turbo-q5_0	1	1	211.44	1.73	0.90	0.04	6a94163

Flash Attention OFF:

GPU	Config	Model	Th	FA	Enc.	Dec.	Bch5	PP	Commit
M2 Ultra	METAL	tiny	1	0	10.04	1.37	0.50	0.01	6a94163
M2 Ultra	METAL	tiny-q5_0	1	0	10.02	1.36	0.53	0.01	6a94163
M2 Ultra	METAL	tiny-q5_1	1	0	11.08	1.37	0.53	0.01	6a94163
M2 Ultra	METAL	base	1	0	17.84	1.93	0.77	0.02	6a94163
M2 Ultra	METAL	base-q5_0	1	0	18.57	1.92	0.81	0.02	6a94163
M2 Ultra	METAL	base-q5_1	1	0	18.66	1.93	0.82	0.02	6a94163
M2 Ultra	METAL	small	1	0	48.26	3.95	1.73	0.05	6a94163
M2 Ultra	METAL	small-q5_0	1	0	53.68	3.99	1.85	0.06	6a94163
M2 Ultra	METAL	small-q5_1	1	0	53.86	4.00	1.82	0.06	6a94163
M2 Ultra	METAL	medium	1	0	130.09	8.01	3.82	0.13	6a94163
M2 Ultra	METAL	medium-q5_0	1	0	148.18	7.92	4.11	0.14	6a94163
M2 Ultra	METAL	medium-q5_1	1	0	147.95	7.94	4.11	0.14	6a94163
M2 Ultra	METAL	medium-dis	1	0	116.97	1.11	0.42	0.02	6a94163
M2 Ultra	METAL	large-v2	1	0	232.43	12.34	5.87	0.22	6a94163
M2 Ultra	METAL	large-v2-q5_0	1	0	269.72	11.68	6.44	0.26	6a94163
M2 Ultra	METAL	large-v2-q5_1	1	0	269.71	11.82	6.36	0.26	6a94163
M2 Ultra	METAL	large-v2-dis	1	0	209.25	1.25	0.48	0.02	6a94163
M2 Ultra	METAL	large-v3-turbo	1	0	211.09	1.98	0.84	0.03	6a94163
M2 Ultra	METAL	large-v3-turbo-q5_0	1	0	244.23	1.81	0.92	0.04	6a94163

Ryzen 9 5950X + RTX 2060

Flash Attention ON:

GPU	Config	Model	Th	FA	Enc.	Dec.	Bch5	PP	Commit
RTX 2060	AVX2 CUDA	tiny	1	1	7.35	0.78	0.24	0.01	6a94163
RTX 2060	AVX2 CUDA	tiny-q5_0	1	1	6.45	0.67	0.14	0.01	6a94163
RTX 2060	AVX2 CUDA	tiny-q5_1	1	1	6.39	0.66	0.14	0.01	6a94163
RTX 2060	AVX2 CUDA	base	1	1	10.20	0.88	0.30	0.01	6a94163
RTX 2060	AVX2 CUDA	base-q5_0	1	1	11.38	0.92	0.21	0.02	6a94163
RTX 2060	AVX2 CUDA	base-q5_1	1	1	11.76	0.91	0.20	0.02	6a94163
RTX 2060	AVX2 CUDA	small	1	1	33.06	2.00	0.56	0.03	6a94163
RTX 2060	AVX2 CUDA	small-q5_0	1	1	35.84	1.84	0.43	0.04	6a94163
RTX 2060	AVX2 CUDA	small-q5_1	1	1	36.89	1.82	0.42	0.04	6a94163
RTX 2060	AVX2 CUDA	medium	1	1	90.65	4.54	1.13	0.08	6a94163
RTX 2060	AVX2 CUDA	medium-q5_0	1	1	104.01	3.80	0.91	0.10	6a94163
RTX 2060	AVX2 CUDA	medium-q5_1	1	1	107.98	3.72	0.87	0.10	6a94163
RTX 2060	AVX2 CUDA	medium-dis	1	1	79.08	0.68	0.17	0.01	6a94163
RTX 2060	AVX2 CUDA	large-v2	1	1	162.00	7.52	1.92	0.14	6a94163
RTX 2060	AVX2 CUDA	large-v2-q5_0	1	1	184.59	5.64	1.50	0.16	6a94163
RTX 2060	AVX2 CUDA	large-v2-q5_1	1	1	193.85	5.55	1.44	0.17	6a94163
RTX 2060	AVX2 CUDA	large-v2-dis	1	1	140.75	0.84	0.37	0.02	6a94163
RTX 2060	AVX2 CUDA	large-v3-turbo	1	1	143.38	1.29	0.36	0.02	6a94163
RTX 2060	AVX2 CUDA	large-v3-turbo-q5_0	1	1	163.30	0.93	0.28	0.03	6a94163

Flash Attention OFF:

GPU	Config	Model	Th	FA	Enc.	Dec.	Bch5	PP	Commit
RTX 2060	AVX2 CUDA	tiny	1	0	12.49	0.87	0.23	0.01	6a94163
RTX 2060	AVX2 CUDA	tiny-q5_0	1	0	10.65	0.78	0.19	0.02	6a94163
RTX 2060	AVX2 CUDA	tiny-q5_1	1	0	10.82	0.77	0.19	0.02	6a94163
RTX 2060	AVX2 CUDA	base	1	0	18.97	1.04	0.34	0.02	6a94163
RTX 2060	AVX2 CUDA	base-q5_0	1	0	20.22	1.09	0.27	0.02	6a94163
RTX 2060	AVX2 CUDA	base-q5_1	1	0	20.48	1.07	0.27	0.02	6a94163
RTX 2060	AVX2 CUDA	small	1	0	59.52	2.37	0.70	0.05	6a94163
RTX 2060	AVX2 CUDA	small-q5_0	1	0	62.98	2.23	0.60	0.06	6a94163
RTX 2060	AVX2 CUDA	small-q5_1	1	0	63.64	2.21	0.59	0.06	6a94163
RTX 2060	AVX2 CUDA	medium	1	0	161.53	5.36	1.53	0.13	6a94163
RTX 2060	AVX2 CUDA	medium-q5_0	1	0	174.96	4.64	1.32	0.15	6a94163
RTX 2060	AVX2 CUDA	medium-q5_1	1	0	178.42	4.57	1.29	0.15	6a94163
RTX 2060	AVX2 CUDA	medium-dis	1	0	149.65	0.75	0.20	0.02	6a94163
RTX 2060	AVX2 CUDA	large-v2	1	0	280.55	8.74	2.51	0.23	6a94163
RTX 2060	AVX2 CUDA	large-v2-q5_0	1	0	306.87	6.92	2.08	0.25	6a94163
RTX 2060	AVX2 CUDA	large-v2-q5_1	1	0	314.25	6.82	2.02	0.26	6a94163
RTX 2060	AVX2 CUDA	large-v2-dis	1	0	259.39	0.91	0.37	0.02	6a94163
RTX 2060	AVX2 CUDA	large-v3-turbo	1	0	261.83	1.44	0.41	0.04	6a94163
RTX 2060	AVX2 CUDA	large-v3-turbo-q5_0	1	0	282.99	1.09	0.33	0.04	6a94163

Vulkan:

GPU	Config	Model	Th	FA	Enc.	Dec.	Bch5	PP	Commit
RTX 2060	VULKAN	tiny	1	0	30.38	1.37	1.04	0.05	9f346d0
RTX 2060	VULKAN	tiny-q5_0	1	0	20.98	1.38	0.99	0.05	9f346d0
RTX 2060	VULKAN	tiny-q5_1	1	0	20.74	1.30	0.96	0.05	9f346d0
RTX 2060	VULKAN	base	1	0	44.69	1.59	1.78	0.09	9f346d0
RTX 2060	VULKAN	base-q5_0	1	0	39.72	2.11	1.72	0.08	9f346d0
RTX 2060	VULKAN	base-q5_1	1	0	39.45	2.01	1.63	0.08	9f346d0
RTX 2060	VULKAN	small	1	0	160.02	3.53	4.64	0.23	9f346d0
RTX 2060	VULKAN	small-q5_0	1	0	141.52	4.54	4.44	0.20	9f346d0
RTX 2060	VULKA...

v1.6.2

Overview

Bugfix when using multiple whisper_state in parallel: #2182

What's Changed

• Update ruby bindings by @taf2 in #2154
• Update server.cpp by @dvaldivia in #2181
• Revert "whisper : remove extra backend instance (huh?)" by @ggerganov in #2182

New Contributors

• @dvaldivia made their first contribution in #2181

Full Changelog: v1.6.1...v1.6.2

v1.6.1

Minor release adding initial ffmpeg support in the examples #2133 (thx @WilliamTambellini)

What's Changed

• ci: Update build.yml to suppress warnings about node.js versions by @tamo in #2166
• node : add flash_attn param by @pprobst in #2170
• Add support for decoding input with ffmpeg (Linux) by @WilliamTambellini in #2133

New Contributors

• @WilliamTambellini made their first contribution in #2133

Full Changelog: v1.6.0...v1.6.1

v1.6.0

Overview

• Can optionally enable Flash Attention for faster processing on CUDA and Metal devices (#2152)
• Faster ppc64 performance (40aeeee) (not tested)
• Fix main slowdown bug (#2070)

Shoutout to @JohannesGaessler for contributing efficient FA CUDA kernels

Some performance numbers for this release:

M1 Pro

CPU	Config	Model	Th	FA	Enc.	Dec.	Bch5	PP	Commit
M1 Pro	METAL	tiny	1	0	39.21	1.74	0.61	0.04	22c96b4
M1 Pro	METAL	base	1	0	70.76	2.60	0.93	0.06	22c96b4
M1 Pro	METAL	small	1	0	217.28	6.42	2.14	0.17	22c96b4
M1 Pro	METAL	medium	1	0	596.74	14.43	4.75	0.45	22c96b4

CPU	Config	Model	Th	FA	Enc.	Dec.	Bch5	PP	Commit
M1 Pro	METAL	tiny	1	1	30.77	1.59	0.54	0.03	22c96b4
M1 Pro	METAL	base	1	1	60.42	2.29	0.81	0.05	22c96b4
M1 Pro	METAL	small	1	1	183.82	5.12	1.81	0.14	22c96b4
M1 Pro	METAL	medium	1	1	517.92	11.60	4.01	0.38	22c96b4

M2 Ultra

CPU	Config	Model	Th	FA	Enc.	Dec.	Bch5	PP	Commit
M2 ULTRA	METAL	tiny	1	0	12.32	1.35	0.49	0.01	22c96b4
M2 ULTRA	METAL	tiny-q5_0	1	0	11.65	1.30	0.51	0.01	22c96b4
M2 ULTRA	METAL	tiny-q5_1	1	0	12.08	1.30	0.51	0.01	22c96b4
M2 ULTRA	METAL	base	1	0	17.58	1.90	0.76	0.02	22c96b4
M2 ULTRA	METAL	base-q5_0	1	0	18.89	1.86	0.79	0.02	22c96b4
M2 ULTRA	METAL	base-q5_1	1	0	20.69	1.88	0.79	0.02	22c96b4
M2 ULTRA	METAL	small	1	0	49.32	3.85	1.71	0.05	22c96b4
M2 ULTRA	METAL	small-q5_0	1	0	54.91	3.81	1.82	0.06	22c96b4
M2 ULTRA	METAL	small-q5_1	1	0	54.92	3.81	1.79	0.06	22c96b4
M2 ULTRA	METAL	medium	1	0	134.34	8.04	3.82	0.13	22c96b4
M2 ULTRA	METAL	medium-q5_0	1	0	151.68	7.59	4.07	0.14	22c96b4
M2 ULTRA	METAL	medium-q5_1	1	0	151.58	7.67	4.07	0.14	22c96b4
M2 ULTRA	METAL	medium-dis	1	0	120.82	1.07	0.41	0.02	22c96b4
M2 ULTRA	METAL	large-v2	1	0	235.63	12.27	5.85	0.22	22c96b4
M2 ULTRA	METAL	large-v2-q5_0	1	0	273.38	11.17	6.40	0.26	22c96b4
M2 ULTRA	METAL	large-v2-q5_1	1	0	272.44	11.32	6.29	0.26	22c96b4
M2 ULTRA	METAL	large-v2-dis	1	0	212.51	1.20	0.47	0.02	22c96b4

CPU	Config	Model	Th	FA	Enc.	Dec.	Bch5	PP	Commit
M2 ULTRA	METAL	tiny	1	1	9.07	1.33	0.45	0.01	22c96b4
M2 ULTRA	METAL	tiny-q5_0	1	1	9.74	1.33	0.47	0.01	22c96b4
M2 ULTRA	METAL	tiny-q5_1	1	1	8.93	1.31	0.46	0.01	22c96b4
M2 ULTRA	METAL	base	1	1	15.75	1.87	0.71	0.02	22c96b4
M2 ULTRA	METAL	base-q5_0	1	1	17.04	1.83	0.74	0.02	22c96b4
M2 ULTRA	METAL	base-q5_1	1	1	17.17	1.83	0.74	0.02	22c96b4
M2 ULTRA	METAL	small	1	1	42.33	3.64	1.60	0.05	22c96b4
M2 ULTRA	METAL	small-q5_0	1	1	47.61	3.63	1.70	0.05	22c96b4
M2 ULTRA	METAL	small-q5_1	1	1	47.70	3.66	1.68	0.05	22c96b4
M2 ULTRA	METAL	medium	1	1	114.42	7.53	3.55	0.11	22c96b4
M2 ULTRA	METAL	medium-q5_0	1	1	132.63	7.02	3.77	0.13	22c96b4
M2 ULTRA	METAL	medium-q5_1	1	1	132.28	7.10	3.76	0.13	22c96b4
M2 ULTRA	METAL	medium-dis	1	1	102.34	1.01	0.42	0.01	22c96b4
M2 ULTRA	METAL	large-v2	1	1	203.01	11.03	5.45	0.20	22c96b4
M2 ULTRA	METAL	large-v2-q5_0	1	1	240.05	10.18	5.98	0.23	22c96b4
M2 ULTRA	METAL	large-v2-q5_1	1	1	239.22	10.23	5.87	0.23	22c96b4
M2 ULTRA	METAL	large-v2-dis	1	1	181.14	1.14	0.48	0.02	22c96b4

Ryzen 9 5950X + RTX 2060

CPU	Config	Model	Th	FA	Enc.	Dec.	Bch5	PP	Commit
Ryzen 9 5950X	AVX2	tiny	8	0	195.29	1.57	0.51	0.26	22c96b4
Ryzen 9 5950X	AVX2	tiny-q5_0	8	0	213.33	1.10	0.50	0.30	22c96b4
Ryzen 9 5950X	AVX2	tiny-q5_1	8	0	219.38	1.18	0.53	0.32	22c96b4
Ryzen 9 5950X	AVX2	base	8	0	424.85	3.71	1.03	0.46	22c96b4
Ryzen 9 5950X	AVX2	base-q5_0	8	0	473.61	1.81	0.82	0.52	22c96b4
Ryzen 9 5950X	AVX2	base-q5_1	8	0	484.14	1.92	0.85	0.56	22c96b4
Ryzen 9 5950X	AVX2	small	8	0	1458.32	12.66	3.09	1.26	22c96b4
Ryzen 9 5950X	AVX2	small-q5_0	8	0	1673.22	6.42	2.18	1.45	22c96b4
Ryzen 9 5950X	AVX2	small-q5_1	8	0	1724.78	6.72	2.32	1.52	22c96b4
Ryzen 9 5950X	AVX2	medium	8	0	4333.87	36.80	8.56	3.37	22c96b4
Ryzen 9 5950X	AVX2	medium-q5_0	8	0	5194.09	19.21	5.71	3.97	22c96b4
Ryzen 9 5950X	AVX2	medium-q5_1	8	0	5450.39	20.01	5.99	4.17	22c96b4
Ryzen 9 5950X	AVX2	medium-dis	8	0	3995.19	5.08	1.21	0.55	22c96b4
Ryzen 9 5950X	AVX2	large-v2	8	0	8056.16	69.74	16.11	6.13	22c96b4
Ryzen 9 5950X	AVX2	large-v2-q5_0	8	0	9799.58	35.16	10.49	7.28	22c96b4
Ryzen 9 5950X	AVX2	large-v2-q5_1	8	0	ms	36.74	11.02	7.65	22c96b4
Ryzen 9 5950X	AVX2	large-v2-dis	8	0	7490.03	7.40	1.70	0.72	22c96b4

GPU	Config	Model	Th	FA	Enc.	Dec.	Bch5	PP	Commit
RTX 2060	AVX2 CUDA	tiny	8	0	12.54	0.93	0.29	0.02	22c96b4
RTX 2060	AVX2 CUDA	tiny-q5_0	8	0	12.73	0.98	0.24	0.02	22c96b4
RTX 2060	AVX2 CUDA	tiny-q5_1	8	0	12.72	0.99	0.24	0.02	22c96b4
RTX 2060	AVX2 CUDA	base	8	0	24.14	1.28	0.41	0.03	22c96b4
RTX 2060	AVX2 CUDA	base-q5_0	8	0	24.58	1.38	0.35	0.03	22c96b4
RTX 2060	AVX2 CUDA	base-q5_1	8	0	24.58	1.37	0.35	0.03	22c96b4
RTX 2060	AVX2 CUDA	small	8	0	74.70	2.91	0.84	0.07	22c96b4
RTX 2060	AVX2 CUDA	small-q5_0	8	0	76.12	2.84	0.77	0.08	22c96b4
RTX 2060	AVX2 CUDA	small-q5_1	8	0	76.14	2.84	0.76	0.08	22c96b4
RTX 2060	AVX2 CUDA	medium	8	0	200.69	6.46	1.83	0.17	22c96b4
RTX 2060	AVX2 CUDA	medium-q5_0	8	0	204.80	5.90	1.65	0.19	22c96b4
RTX 2060	AVX2 CUDA	medium-q5_1	8	0	205.61	5.85	1.61	0.19	22c96b4
RTX 2060	AVX2 CUDA	medium-dis	8	0	186.17	0.86	0.24	0.02	22c96b4
RTX 2060	AVX2 CUDA	large-v2	8	0	347.22	10.36	2.82	0.29	22c96b4
RTX 2060	AVX2 CUDA	large-v2-q5_0	8	0	357.06	8.81	2.58	0.34	22c96b4
RTX 2060	AVX2 CUDA	large-v2-q5_1	8	0	356.97	8.62	2.49	0.33	22c96b4
RTX 2060	AVX2 CUDA	large-v2-dis	8	0	318.05	1.03	0.34	0.04	22c96b4

GPU	Config	Model	Th	FA	Enc.	Dec.	Bch5	PP	Commit
RTX 2060	AVX2 CUDA	tiny	8	1	7.21	0.76	0.29	0.02	22c96b4
RTX 2060	AVX2 CUDA	tiny-q5_0	8	1	7.42	0.82	0.18	0.02	22c96b4
RTX 2060	AVX2 CUDA	tiny-q5_1	8	1	7.38	0.82	0.18	0.02	22c96b4
RTX 2060	AVX2 CUDA	...

v1.5.5

Overview

Many small incremental updates + Token level timestamps with DTW by @denersc in #1485
Feedback is welcome!

Full Changelog: v1.5.4...v1.5.5

What's Changed

• server : fix server temperature + add temperature_inc by @ggerganov in #1729
• main : add cli option to disable system prints by @ggerganov in #1740
• server: add request path by @eschmidbauer in #1741
• Optional Piper TTS support for talk-llama example. by @RhinoDevel in #1749
• fix/1748 by @nank1ro in #1750
• Don't compute timestamps when not printing them. by @ghindle in #1755
• Add more parameters to server api by @ghindle in #1754
• Add SetInitialPrompt method to go bindings by @blib in #1753
• ggml : fix 32-bit ARM compat for IQ2_XS by @ggerganov in #1758
• refactor: get all scripts to be POSIX Compliant by @sonphantrung in #1725
• whisper : load the model into multiple buffers of max size 1GB by @ggerganov in #1763
• rebase against your -np changes (thx) and add better python file to be used on the command line or as library by @contractorwolf in #1744
• examples/talk-llama: Add optional commandline parameter to set the bot name. by @RhinoDevel in #1764
• server : fix building and simplify lib deps on Windows by @przemoc in #1772
• talk-llama: optional wake-up command and audio confirmation by @Rakksor in #1765
• examples/server: implement "verbose_json" format with token details by @rmmh in #1781
• whisper.android: Return output from benchmarks by @luciferous in #1785
• libwhisper.so should be position independent by @trixirt in #1792
• Docs: try to make model options / model install methods clearer by @mrienstra in #1806
• common : fix input buffer check by @ggerganov in #1812
• Update Makefile by @jwijffels in #1813
• Add fields to verbose_json response and show examples on the home page by @JacobLinCool in #1802
• common: fix wav buffer detection by @JacobLinCool in #1819
• Add macOS deployment target option to Makefile by @didzis in #1839
• Expose CUDA device setting in public API by @didzis in #1840
• whisper.android: How to build with CLBlast by @luciferous in #1809
• server: Allow CORS request with authorization headers by @valenting in #1850
• Embed Metal library source into compiled binary by @didzis in #1842
• added audio_ctx argument to main and server examples by @dscripka in #1857
• whisper : fix external encoder by @ggerganov in #1860
• swift : package no longer use ggml dependency by @ggerganov in #1861
• fix openvino setup docs by @jumpers775 in #1874
• clean up common code in examples by @felrock in #1871
• main : check if input files exist before proceeding by @Theldus in #1872
• Linking issue fix via Makefile when CUBLAS enabled in the WSL #1876 by @lbluep in #1878
• main : fix file existence check in main.cpp by @Theldus in #1889
• openvino : fix convert-whisper-to-openvino.py for v2023.0.0 (#1870) by @st-gr in #1890
• ggml : 32-bit arm compat by @ggerganov in #1891
• Add SYCL logic in whisper by @abhilash1910 in #1863
• talk and talk-llama: Pass text_to_speak as a file by @tamo in #1865
• Stream.wasm: Fix invalid memory access when no segments are returned by @Andrews54757 in #1902
• Update README to Recommend MacOS Sonoma for Core ML to avoid hallucination by @gavin1818 in #1917
• Add library versioning by @kenneth-ge in #1352
• Fix SF(segment fault) issue in Android JNI by @zhouwg in #1929
• Fix typo in source file whisper.cpp by @zhouwg in #1925
• bench:fix typo by @zhouwg in #1933
• Auto lowercase language parameter by @F1L1Pv2 in #1928
• ggml : try fix 32-bit arm compat by @ggerganov in #1938
• whisper : make beam candidate sort more stable by @josharian in #1943
• bindings/go : add linker flags to make metal work by @josharian in #1944
• whisper : improve beam search candidate diversity by @josharian in #1947
• whisper : document whisper_batch.n_seq_id by @josharian in #1942
• Rename --audio-context to --audio-ctx, as per help text by @joliss in #1953
• [DRAFT] Token level timestamps with DTW (#375) by @denersc in #1485
• Fedora dependencies needed (SDL2) by @Man2Dev in #1970
• libcuda.so.1 in PATH in Docker Container by @tiagofassoni in #1966
• ruby : fix build by @ggerganov in #1980
• Improve support for distil-large-v3 by @sanchit-gandhi in #1982
• whisper : improve handling of prompts by @ggerganov in #1981
• sync : ggml by @ggerganov in #2001
• Implemented command-style grammar in the main example. by @ulatekh in #1998
• Use pkg-config for OpenBLAS by @przemoc in #1778
• ci : add building in MSYS2 environments (Windows) by @przemoc in #1994
• Support CUDA versions < 11.1 by @primenko-v in #2020
• Create solution folders in the CMake build by @ulatekh in #2004
• Allow a regular expression to describe tokens to suppress by @ulatekh in #1997
• "main" example now allows a response-file as the sole parameter by @ulatekh in #2019
• Support for CPU BLAS build via Intel MKL by @slashlib in #2024
• Set stdin to binary mode on Windows. Fixes #2023 by @rotemdan in #2025
• Fix file-handle leak in read_wav() by @ulatekh in #2026
• Fix DTW memory access by @bradmurray-dt in #2012
• whisper: update grammar-parser.cpp by @eltociear in #2058
• fix missing reference to "model" variable in actual shell command run in whisper.nvim by @sixcircuit in #2049
• build : detect AVX512 in Makefile, add AVX512 option in CMake by @didzis in #2043
• feature/no timestamps node by @pprobst in #2048
• Update embedded Metal library generation process to include dependency by @didzis in #2045
• server.cpp: add dtw by @eschmidbauer in #2044

New Contributors

• @eschmidbauer made their first contribution in #1741
• @RhinoDevel made their first contribution in #1749
• @nank1ro made their first contribution in #1750
• @ghindle made their first contribution in #1755
• @blib made their first contribution in #1753
• @sonphantrung made their first contribution in #1725
• @contractorwolf made their first contribution in #1744
• @Rakksor made their first contribution in #1765
• @rmmh made their f...

v1.5.4

Overview

• Faster Core ML ANE models (#1716)
• CUDA bugfix causing random erros in the transcription
• Fix SwiftUI example build

Full Changelog: v1.5.3...v1.5.4

v1.5.3

Overview

Minor maintenance release:

• Fix CUDA issues where the transcription produces garbage
• FIX quantized models to work with CUDA backend
• Allow to use whisper.cpp and llama.cpp together in SwiftUI projects

What's Changed

• Update bench.py by @ForkedInTime in #1655
• cmake : Resolve quantized model issue when CUBLAS enabled by @bobqianic in #1667
• examples : Revert CMakeLists.txt for talk-llama by @bobqianic in #1669
• CI : Add coverage for talk-llama when WHISPER_CUBLAS=1 by @bobqianic in #1672
• ci: build and push docker image by @OpenWaygate in #1674
• sync : ggml (ggml_scale, ggml_row_size, etc.) by @ggerganov in #1677
• Replace WHISPER_PRINT_DEBUG with WHISPER_LOG_DEBUG by @bobqianic in #1681
• download: Fix large q5 model name by @dimopep in #1695
• sync : ggml (VMM, sync-ggml-am.sh, dotprod ARM fixes) by @ggerganov in #1691
• whisper : replace tensor->n_dims with ggml_n_dims(tensor) by @bobqianic in #1694
• Build with CLBlast by @tamo in #1576
• docker : Fix the Publishing of the CUDA Docker Image by @bobqianic in #1704
• emscripten: fix "Stack Overflow!" by @Huguet57 in #1713
• sync : ggml by @ggerganov in #1717
• Add error handling to graph_compute by @finnvoor in #1714
• Updates Package.swift to use ggml as package dependency by @1-ashraful-islam in #1701

New Contributors

• @ForkedInTime made their first contribution in #1655
• @OpenWaygate made their first contribution in #1674
• @dimopep made their first contribution in #1695
• @Huguet57 made their first contribution in #1713
• @1-ashraful-islam made their first contribution in #1701

Full Changelog: v1.5.2...v1.5.3

v1.5.2

Overview

Minor maintenance release:

• Re-enable CPU BLAS processing after fixing a regression (#1583)

Add new example: wchess

wchess-0.mp4

Shoutout to @fraxy-v (implementation) and @ejones (grammar) for making it work!

What's Changed

• automatically convert audio on the server by @sapoepsilon in #1539
• CI : Rectify the Clang-Related workflow issues by @bobqianic in #1551
• CI : Add CUDA 11.8.0 support by @bobqianic in #1554
• Update main program help info by @bebound in #1560
• Set default CORS headers to allow all by @kasumi-1 in #1567
• cmake : install required ggml.h header by @gjasny in #1568
• Backport .srt output format to examples/server by @osdrv in #1565
• Added support for .vtt format to Whisper server by @aleksanderandrzejewski in #1578
• ggml : re-enable blas for src0 != F32 by @ggerganov in #1583
• Fix 32-bit compiler warning by @Digipom in #1575
• Remove #if arch(arm) check in Swift Package Manager by @finnvoor in #1561
• Pass max-len argument to server wparams by @osdrv in #1574
• sync : ggml (new ops, new backend, etc) by @ggerganov in #1602
• Fix ggml_metal_log on Intel macs by @finnvoor in #1606
• Update CMakeLists.txt by @Kreijstal in #1615
• target windows 8 or above for prefetchVirtualMemory in llama-talk by @Kreijstal in #1617
• sync : ggml (Metal fixes, new ops, tests) by @ggerganov in #1633
• wchess: whisper assisted chess by @fraxy-v in #1595

New Contributors

• @sapoepsilon made their first contribution in #1539
• @bebound made their first contribution in #1560
• @kasumi-1 made their first contribution in #1567
• @gjasny made their first contribution in #1568
• @osdrv made their first contribution in #1565
• @aleksanderandrzejewski made their first contribution in #1578
• @Kreijstal made their first contribution in #1615
• @fraxy-v made their first contribution in #1595

Full Changelog: v1.5.1...v1.5.2

v1.5.1

Overview

Minor update:

• With Metal, auto-fallback to CPU if device does not support Apple7 family
• Add server example

What's Changed

• ISSUE-1329: replace " with ' so it doesn't try to execute code in backticks by @spullara in #1364
• sync : ggml (ggml-alloc + linker + gguf fixes) by @ggerganov in #1501
• Fixed with_state methods, to use the correct state by @sandrohanea in #1519
• #1517 Redistribute CUDA DLLs by @tamo in #1522
• whisper : reuse whisper_decode_with_state by @ggerganov in #1521
• sdl : fix audio callback by @ggerganov in #1523
• update deprecated example by @MightyStud in #1529
• Super Simple Whisper Server by @felrock in #1380
• Close file after writing in server application by @felrock in #1533
• bench : multi-thread memcpy by @ggerganov in #1534
• Change temp file name for server application by @felrock in #1535
• Fixed Makefile for MacOS ARM 64 Go bindings by @gleicon in #1530
• Fixed metal build on macos-latest by @sandrohanea in #1544
• fix(server): typo in temperature parameter by @Okabintaro in #1545
• Request to add a new function to get the full language name by @bradmit in #1546
• server : add --print-realtime param by @ecneladis in #1541
• cuda : sync some minor stuff from llama.cpp by @ggerganov in #1548
• metal : add backend function to check device family support by @ggerganov in #1547

New Contributors

• @spullara made their first contribution in #1364
• @MightyStud made their first contribution in #1529
• @felrock made their first contribution in #1380
• @gleicon made their first contribution in #1530
• @Okabintaro made their first contribution in #1545
• @bradmit made their first contribution in #1546
• @ecneladis made their first contribution in #1541

Full Changelog: v1.5.0...v1.5.1