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llm-speed

Cheatsheet

Local LLM speed cheatsheet: decode tok/s by GPU & Mac

Best decode tokens-per-second per (model × hardware) tuple measured by llm-speed under suite-v1. Numbers are wall-clock, batch size 1 unless the workload says otherwise. Each row links to the canonical run page; cite as llm-speed.com/r/<id>.

157 (model × hardware) combinations · sorted by decode tok/s · suite-v1

Long documents and bulk extraction

For long inputs with short answers, compare prefill, time to first token and total request time at your input length, cache state and concurrency. Check extraction accuracy too. This table selects the fastest decode row per model and hardware pair; its prefill and TTFT columns describe that row, not the best prefill speed or lowest latency.

Start with the prefill vs decode guide or the measured Gemma 4 long-context study to see how input length changes the wait before streaming.

ModelQuantHardwareBackendWorkloaddecode tok/sprefill tok/sTTFT (ms)Run
llama3.2Q8_0RTX 5880 (48GB)ollama@0.34.2chat-short466.944.32820.6r_b948ehgi8g4
mlx-community/Qwen3-0.6B-4bit-M3 Ultra (60-core GPU) + 96GB unifiedmlx@0.31.3chat-short429.21185.292.8r_6rgao6ao735
stable-code-instruct-3b-RTX 5090 (32GB)llama.cppconcurrent-decode356.1——r_q9f15lz6831
gpt-oss-20bQ4_K_MRTX 5090 (32GB)llama.cpp@0.7.0-dev (build 1, commit 1268eda)chat-short324.2586.8282.9r_dwp5fgdapmw
LFM2.5-24B-A2BQ4_K_MRTX 5090 (32GB)llama.cpp@0.6.0-dev (build 1, commit a0e6dc7)concurrent-decode321.3——r_c8k6fleym09
DeepSeek-Coder-V2-Lite-Instruct-RTX 5090 (32GB)llama.cppchat-short309.5—267.6r_0_gs1rgl2fl
Qwen3-Coder-30B-A3B-InstructQ4_K_MRTX 5090 (32GB)llama.cpp@0.7.0-dev (build 1, commit 1268eda)chat-short304.9514.5213.8r_vsype4pm1ko
mlx-community-Qwen2.5-0.5B-Instruct-4bit4bitM3 Pro (18-core GPU) + 36GB unifiedmlx@0.31.3chat-short286.5656.2199.6r_akcbpx5vcqa
Qwen2.5-Coder-7B-Instruct-RTX 5090 (32GB)llama.cppchat-short255.3—35.4r_2b9o6y_49mi
Qwen2.5-7B-Instruct-RTX 5090 (32GB)llama.cppchat-short246.7—33.9r_3yn-4321hp-
gpt-oss-20bQ4_K_MRTX 4090 (24GB)llama.cpp@0.6.0-dev (build 1, commit df18bee)chat-short242.6593.8279.5r_t-a9v_ipdit
LFM2.5-24B-A2BQ4_K_MRTX 4090 (24GB)llama.cpp@0.6.0-dev (build 1, commit a0e6dc7)concurrent-decode236.8——r_bqmpv9kncyd
Qwen3-Coder-30B-A3B-InstructQ4_K_MRTX 4090 (24GB)llama.cpp@0.6.0-dev (build 1, commit df18bee)chat-short232.5831.9132.2r_1k8942tw3zf
Llama-3.1-8B-Instruct-RTX 5090 (32GB)llama.cppchat-short232.2—33.8r_kfrkg-vn376
Qwen3.6-35B-A3B-Q4_K_M.gguf-RTX 5090 (32GB)llama.cppchat-short224.0—169.5r_g1aw3mizd32
Sage-A1.5-ctx48kQ4_K_MRTX 4090 (24GB)llama.cpp@0.7.0-dev (build 11803, commit a37cc4610)concurrent-decode217.2——r_izwoxrsouc4
Sage-A1.5-ctx8kQ4_K_MRTX 4090 (24GB)llama.cpp@0.7.0-dev (build 11803, commit a37cc4610)concurrent-decode216.9——r_4x-4g-xhhgk
Sage-A1.5-ctx128kQ4_K_MRTX 4090 (24GB)llama.cpp@0.7.0-dev (build 11803, commit a37cc4610)chat-short216.81023.9109.4r_-i4k-ieitrk
Sage-A1.5-ctx32kQ4_K_MRTX 4090 (24GB)llama.cpp@0.7.0-dev (build 11803, commit a37cc4610)chat-short216.81023.6109.4r_9uktwjj22y-
Sage-A1.5-ctx64kQ4_K_MRTX 4090 (24GB)llama.cpp@0.7.0-dev (build 11803, commit a37cc4610)chat-short216.61042.3107.5r_vusd3gw5tpg
Sage-A1.5-ctx96kQ4_K_MRTX 4090 (24GB)llama.cpp@0.7.0-dev (build 11803, commit a37cc4610)concurrent-decode216.6——r_5nh2jxjbzur
Sage-A1.5-ctx16kQ4_K_MRTX 4090 (24GB)llama.cpp@0.7.0-dev (build 11803, commit a37cc4610)chat-short216.6991.6113.0r_anosq1xr6tc
gpt-oss-20bQ4_K_MRTX 3090 (24GB)llama.cpp@0.7.0-dev (build 1, commit ea0c4c2)chat-short207.2658.3252.1r_nakw1nq6clw
Qwen3-Coder-30B-A3B-InstructQ4_K_MRTX 3090 (24GB)llama.cpp@0.7.0-dev (build 1, commit ea0c4c2)chat-short199.7612.5179.6r_0dh1kzbv4h0
Yi-Coder-9B-Chat-RTX 5090 (32GB)llama.cppchat-short199.3—36.2r_u4iojm6-ekg
gemma3Q4_K_MRTX 4090 (24GB)ollama@0.31.1chat-short195.0167.2705.6r_dlanfbgym0h
mlx-community/stable-code-instruct-3b-4bit-M3 Ultra (60-core GPU) + 96GB unifiedmlx@0.31.3chat-short192.5560.7226.5r_y2_5y8oo97d
deepseek-coder-v2Q4_0RTX 3090 (24GB)ollama@0.31.1chat-short189.5159.2734.9r_o2-1w665rtq
mlx-community/Qwen3-4B-Instruct-2507-4bit-M3 Ultra (60-core GPU) + 96GB unifiedmlx@0.31.3chat-short182.7636.6172.8r_p2rpb_0iyjj
qwen3-coderQ4_K_MRTX 4090 (24GB)ollama@0.31.1concurrent-decode179.9——r_wjq32z47vlp
Flint-40B-A2.5B-NVFP4-RTX 4090 (24GB)llama.cpp@0.7.0-dev (build 11803, commit a37cc4610)chat-short179.4423.1231.6r_0i0a9uq6fdx
Flint-40B-A2.5B-UD-ctx16kQ3_K_XLRTX 4090 (24GB)llama.cpp@0.7.0-dev (build 11803, commit a37cc4610)chat-short169.2442.0221.7r_sw92j6kg7js
mlx-community/DeepSeek-Coder-V2-Lite-Instruct-4bit-M3 Ultra (60-core GPU) + 96GB unifiedmlx@0.31.3chat-short168.3291.5449.5r_l_v1-zq_qaz
Flint-40B-A2.5B-UD-ctx8kQ3_K_XLRTX 4090 (24GB)llama.cpp@0.7.0-dev (build 11803, commit a37cc4610)chat-short168.0488.4200.6r_r7gzl4lmmdc
glm-4.7-flashQ4_K_MRTX 4090 (24GB)ollama@0.31.1chat-short164.93.728105.7r_ted0u8uyre0
Qwen3.6-35B-A3BQ4_K_MRTX 4090 (24GB)llama.cpp@8931 (9725a313b)concurrent-decode163.5——r_m6j1zxwvp-f
qwen2.5-coderQ4_K_MRTX 4090 (48GB)ollama@0.31.1concurrent-decode161.1——r_mv8n8k9wu1e
Meta-Llama-3.1-8B-InstructQ4_K_MRTX 4090 (24GB)llama.cpp@0.7.0-dev (build 11803, commit a37cc4610)chat-short160.84283.131.5r_32ipo1hbbwl
NVIDIA-Nemotron-3.5-Bolt-74B-A9B-24GB-ctx32k-RTX 5090 (32GB)llama.cpp@0.7.0-dev (build 11669, commit 620d2225c)concurrent-decode157.7——r_ymx58emedxd
NVIDIA-Nemotron-3.5-Bolt-74B-A9B-24GB-RTX 5090 (32GB)llama.cpp@0.7.0-dev (build 11669, commit 620d2225c)concurrent-decode156.0——r_z-l1yelv_67
DeepSeek-R1-0528-Qwen3-8BQ4_K_MRTX 4090 (24GB)llama.cpp@0.7.0-dev (build 11803, commit a37cc4610)chat-short155.02106.749.8r_ll6l5npoik8
Qwen3-8BQ4_K_MRTX 4090 (24GB)llama.cpp@0.7.0-dev (build 11803, commit a37cc4610)chat-short155.02155.251.0r_kiilk85gcx_
llama3.1Q4_K_MRTX 4090 (48GB)ollama@0.31.1chat-short154.4328.0335.4r_h1ub_1uxzdh
gemma-2-9b-it-RTX 5090 (32GB)llama.cppchat-short152.7—58.9r__b_bzmmab_8
mlx-community/gpt-oss-20b-MXFP4-Q4-M3 Ultra (60-core GPU) + 96GB unifiedmlx@0.31.3chat-short152.7239.9692.1r_3ijun8ltjnb
LFM2.5-24B-A2BQ4_K_MRTX A4000 (16GB)llama.cpp@0.7.0-dev (build 1, commit b76b133)concurrent-decode142.7——r_j5tgvia-kjk
gemma-4-12b-it-qatQ4_0RTX 5090 (32GB)llama.cpp@1 (9725a31)long-context-decay142.67115.83354.8r_-lh-vczf7ik
gpt-ossMXFP4RTX 4090 (24GB)ollama@0.31.1chat-long141.7631.55048.2r_iu2sfa9ykvw
phi-4-RTX 5090 (32GB)llama.cppchat-short140.9—56.7r_e-k4aea8ipr
Qwen2.5-Coder-14B-Instruct-RTX 5090 (32GB)llama.cppchat-short140.0—42.1r_opuj21f13-_
mlx-community-Qwen2.5-7B-Instruct-4bit4bitM3 Ultra (60-core GPU) + 96GB unifiedmlx@0.31.3chat-short139.6190.0689.4r_5r6rhiynenc
qwen2.5-coderQ4_K_MRTX 3090 (24GB)ollama@0.31.1concurrent-decode139.2——r_pb0jpnbujji
mlx-community/Qwen2.5-Coder-7B-Instruct-4bit-M3 Ultra (60-core GPU) + 96GB unifiedmlx@0.31.3chat-short138.6539.6242.8r_uoehjq0nvc0
llama3.1Q4_K_MRTX 4090 (24GB)ollama@0.31.1chat-short137.3269.1408.8r_2np7abzjobe
qwen2.5-coderQ4_K_MRTX 4090 (24GB)ollama@0.31.1concurrent-decode137.3——r_nrpc8-onxu2
llama3.1Q4_K_MRTX 3090 (24GB)ollama@0.31.1chat-short136.22.249960.0r_9hurqggbshk
glm-4.7-flashQ4_K_MRTX 3090 (24GB)ollama@0.31.1chat-short134.64.324308.6r_kalwcyab-86
deepseek-r1Q4_K_MRTX 4090 (24GB)ollama@0.31.1agent-trace133.88852.4366.2r_fg77v2hhohb
Qwen2.5-14B-Instruct-RTX 5090 (32GB)llama.cppchat-short133.3—55.9r_tj9bu7gvnvh
Flint-40B-A2.5B-UD-ctx8kQ3_K_XLRTX 3090 (24GB)llama.cpp@0.7.0-dev (build 11803, commit a37cc4610)chat-short130.8365.9267.8r_-yeg4qnhjp7
mlx-community/Llama-3.1-8B-Instruct-4bit-M3 Ultra (60-core GPU) + 96GB unifiedmlx@0.31.3chat-short130.2400.3339.7r_v2pbc0rq2l4
Flint-40B-A2.5B-UD-ctx16kQ3_K_XLRTX 3090 (24GB)llama.cpp@0.7.0-dev (build 11803, commit a37cc4610)chat-short128.9371.7263.6r_v-sdiljpm7i
mlx-community/Qwen3-8B-4bit-M3 Ultra (60-core GPU) + 96GB unifiedmlx@0.31.3chat-short120.5446.1246.6r_b1awwhkoo2v
lmstudio-community/DeepSeek-R1-0528-Qwen3-8B-MLX-4bit-M3 Ultra (60-core GPU) + 96GB unifiedmlx@0.31.3chat-short116.8424.5247.4r_yy_6jfx70jq
qwen3-coder-bench-32kQ4_K_MM4 Max (40-core GPU) + 128GB unifiedollama@0.30.11chat-short113.384.11307.7r_roktphpc--8
mlx-community/Qwen3-30B-A3B-Instruct-2507-4bit-M3 Ultra (60-core GPU) + 96GB unifiedmlx@0.31.3chat-short112.5308.7356.3r_o6wbmfegmde
mlx-community/granite-8b-code-instruct-4bit-M3 Ultra (60-core GPU) + 96GB unifiedmlx@0.31.3chat-short112.3525.7220.7r_bue3bee0gw7
mlx-community/Qwen3-Coder-30B-A3B-Instruct-4bit-M3 Ultra (60-core GPU) + 96GB unifiedmlx@0.31.3chat-short112.2204.0539.3r_fpsca03u2o_
qwen3-coderQ4_K_MM4 Max (40-core GPU) + 128GB unifiedollama@0.30.11concurrent-decode109.9——r_r0di2hkku1h
NVIDIA-Nemotron-3.5-Bolt-74B-A9B-24GB-RTX 4090 (24GB)llama.cpp@0.7.0-dev (build 11669, commit 620d2225c)chat-short107.3255.8469.1r_vkjsinuhlyl
NVIDIA-Nemotron-3.5-Bolt-74B-A9B-24GB-ctx8k-RTX 4090 (24GB)llama.cpp@0.7.0-dev (build 11669, commit 620d2225c)chat-short107.0253.3473.7r_iu0s18cs9d8
NVIDIA-Nemotron-3.5-Bolt-74B-A9B-24GB-ctx16k-RTX 4090 (24GB)llama.cpp@0.7.0-dev (build 11669, commit 620d2225c)concurrent-decode105.8——r_qibhq5bkmgq
mlx-community/Yi-Coder-9B-Chat-4bit-M3 Ultra (60-core GPU) + 96GB unifiedmlx@0.31.3chat-short103.5390.9307.0r_3hvui9a1yuc
llama3.2Q8_0M1 Pro (16-core GPU) + 16GB unifiedollama@0.32.14chat-short103.18.814246.7r_w-p7v--eync
Codestral-22B-v0.1-RTX 5090 (32GB)llama.cppconcurrent-decode100.3——r_4q040m4scic
gemma-4-12b-it-qatQ4_0RTX 4090 (24GB)llama.cpp@8931 (9725a313b)chat-short97.71109.0111.8r_jfh0qkngw76
Flint-40B-A2.5B-UD-ctx8kIQ3_XXSRTX A4000 (16GB)llama.cpp@0.7.0-dev (build 11803, commit a37cc4610)chat-short92.9331.7295.5r_e8r7fxw1ke9
Qwen2.5-Coder-14B-InstructQ4_K_MRTX 4090 (24GB)llama.cpp@0.6.0-dev (build 1, commit df18bee)chat-short89.92292.657.1r_eqnsqmgz29a
mlx-community/gemma-2-9b-it-4bit-M3 Ultra (60-core GPU) + 96GB unifiedmlx@0.31.3chat-short89.5170.7691.4r_iz137eqvuzy
Flint-40B-A2.5B-UD-ctx16kIQ3_XXSRTX A4000 (16GB)llama.cpp@0.7.0-dev (build 11803, commit a37cc4610)chat-short89.4327.0299.7r_tp8imqk28q5
qwen3.6-agent-q6k-ctx128kQ6_KM5 Max (40-core GPU) + 48GB unifiedollama@0.32.1chat-short88.316.26915.3r_udwgba7udqu
NVIDIA-Nemotron-3.5-Bolt-74B-A9B-24GB-RTX 3090 (24GB)llama.cpp@0.7.0-dev (build 11669, commit 620d2225c)concurrent-decode87.8——r_-sifd5otbpy
Qwen3.8-27B-mtp-onQ4_K_MRTX 4090 (24GB)llama.cpp@0.6.0-dev (build 1, commit df18bee)concurrent-decode87.0——r_7j8rpk9mwhg
NVIDIA-Nemotron-3.5-Bolt-74B-A9B-24GB-ctx8k-RTX 3090 (24GB)llama.cpp@0.7.0-dev (build 11669, commit 620d2225c)concurrent-decode80.4——r_w3lond-s75t
lmstudio-community-Qwen3-Next-80B-A3B-Instruct-MLX-4bit4bitM3 Ultra (60-core GPU) + 96GB unifiedmlx@0.31.3chat-short80.324.54492.5r_1pl79r50ofy
gemma3Q4_K_MRTX 3090 (24GB)ollama@0.31.1chat-short78.726.04534.1r_3gnxkzhhmyj
Qwen2.5-Coder-14B-InstructQ4_K_MRTX 3090 (24GB)llama.cpp@0.7.0-dev (build 1, commit ea0c4c2)chat-short78.21693.277.4r_rkyf9wxzw9z
Qwen3.8-27BQ4_K_MRTX 5090 (32GB)llama.cpp@0.7.0-dev (build 11669, commit 620d2225c)concurrent-decode75.4——r_qfrb2zmyk0k
Qwen3.6-27BQ4_K_MRTX 5090 (32GB)llama.cpp@0.7.0-dev (build 1, commit 1268eda)concurrent-decode75.1——r_pob-co51bd-
mlx-community/phi-4-4bit-M3 Ultra (60-core GPU) + 96GB unifiedmlx@0.31.3chat-short74.4255.0443.2r_sqzp-0rdez-
Qwen3.6-27B-Q4_K_M.gguf-RTX 5090 (32GB)llama.cppchat-short74.0—190.4r_f7ulllqu4vk
Qwen2.5-Coder-32B-Instruct-RTX 5090 (32GB)llama.cppchat-short71.9—71.0r_nkbs6d3-d21
Qwen2.5-32B-Instruct-RTX 5090 (32GB)llama.cppchat-short71.9—115.2r_twfs86tf_xf
mlx-community-Qwen2.5-14B-Instruct-4bit4bitM3 Ultra (60-core GPU) + 96GB unifiedmlx@0.31.3chat-short70.9301.7434.1r_v4bq1sviz4o
mlx-community/Qwen2.5-Coder-14B-Instruct-4bit-M3 Ultra (60-core GPU) + 96GB unifiedmlx@0.31.3chat-short70.5306.1427.9r_l36cijqxq4t
Qwen3-32BQ4_K_MRTX 5090 (32GB)llama.cpp@0.7.0-dev (build 1, commit 1268eda)chat-short69.81047.0105.1r_vhbqyt1f_xr
gemma-4-31B-it-Q4_K_M.gguf-RTX 5090 (32GB)llama.cppchat-short69.7—174.8r_pa7nuerd9tl
mlx-community/starcoder2-15b-4bit-M3 Ultra (60-core GPU) + 96GB unifiedmlx@0.31.3chat-short64.2220.5489.8r_wsxml_39dh_
Muse-Glimmer-30B-ctx8kUD-Q4_K_XLRTX 4090 (24GB)llama.cpp@0.7.0-dev (build 11803, commit a37cc4610)chat-short53.7655.3235.0r_21z5pn8262x
Muse-Glimmer-30B-ctx32kUD-Q4_K_XLRTX 4090 (24GB)llama.cpp@0.7.0-dev (build 11803, commit a37cc4610)chat-short53.7655.0235.1r_sz089qf84ge
Muse-Glimmer-30B-ctx128kUD-Q4_K_XLRTX 4090 (24GB)llama.cpp@0.7.0-dev (build 11803, commit a37cc4610)chat-short53.7651.7236.3r_jn2059subhm
Muse-Glimmer-30B-ctx48kUD-Q4_K_XLRTX 4090 (24GB)llama.cpp@0.7.0-dev (build 11803, commit a37cc4610)chat-short53.7656.9234.5r_j8qmkq2kd8l
Muse-Glimmer-30B-ctx96kUD-Q4_K_XLRTX 4090 (24GB)llama.cpp@0.7.0-dev (build 11803, commit a37cc4610)chat-short53.7656.2234.7r_xva_h_3wgzn
Muse-Glimmer-30B-ctx64kUD-Q4_K_XLRTX 4090 (24GB)llama.cpp@0.7.0-dev (build 11803, commit a37cc4610)chat-short53.6679.9226.5r_d6vbcmoirgr
Muse-Glimmer-30B-ctx96k-kvq8UD-Q4_K_XLRTX 4090 (24GB)llama.cpp@0.7.0-dev (build 11803, commit a37cc4610)chat-short52.7620.6248.2r_j_abawmxlle
Muse-Glimmer-30B-ctx64k-kvq8UD-Q4_K_XLRTX 4090 (24GB)llama.cpp@0.7.0-dev (build 11803, commit a37cc4610)chat-short52.7685.5224.6r_d1mp5onfwe8
Muse-Glimmer-30B-ctx128k-kvq8UD-Q4_K_XLRTX 4090 (24GB)llama.cpp@0.7.0-dev (build 11803, commit a37cc4610)chat-short52.7614.6250.6r_8dtxula7h35
Muse-Glimmer-30B-ctx32k-kvq8UD-Q4_K_XLRTX 4090 (24GB)llama.cpp@0.7.0-dev (build 11803, commit a37cc4610)chat-short52.7618.7248.9r_g5vn9b96z6e
Muse-Glimmer-30B-ctx48k-kvq8UD-Q4_K_XLRTX 4090 (24GB)llama.cpp@0.7.0-dev (build 11803, commit a37cc4610)chat-short52.7614.6250.6r_7srd_wfvix-
Muse-Glimmer-30B-ctx8k-kvq8UD-Q4_K_XLRTX 4090 (24GB)llama.cpp@0.7.0-dev (build 11803, commit a37cc4610)chat-short52.7617.4249.4r_sbcga8o1-af
mlx-community/Codestral-22B-v0.1-4bit-M3 Ultra (60-core GPU) + 96GB unifiedmlx@0.31.3chat-short47.5205.7559.1r_79dvtag5fd_
Qwen3.6-27BQ4_K_MRTX 4090 (24GB)llama.cpp@0.6.0-dev (build 1, commit 3fb4767)concurrent-decode47.2——r_d_wda_rw62f
qwen3.6Q4_K_MRTX 4090 (48GB)ollama@0.31.1agent-trace44.21910.51807.9r_h_659oy695r
Qwen3.8-27B-ctx8kQ4_K_MRTX 4090 (24GB)llama.cpp@0.7.0-dev (build 11803, commit a37cc4610)chat-short44.2691.5222.7r_tt9io-8lu9p
Qwen3-32BQ4_K_MRTX 4090 (24GB)llama.cpp@0.6.0-dev (build 1, commit df18bee)chat-short43.5778.6141.3r_ayy9rjgha5r
Qwen3.8-27B-ctx4kQ4_K_MRTX 4090 (24GB)llama.cpp@0.7.0-dev (build 11803, commit a37cc4610)chat-short43.4448.3343.6r_7cap38a021-
Qwen3.8-27B-ctx16kQ4_K_MRTX 4090 (24GB)llama.cpp@0.7.0-dev (build 11803, commit a37cc4610)chat-short43.4472.6325.9r_cthpfm82n1r
Qwen3.8-27BQ4_K_MRTX 4090 (24GB)llama.cpp@0.6.0-dev (build 1, commit df18bee)chat-short43.1428.6359.3r_11kn1epxewh
Qwen3.6-27BQ4_K_MRTX 3090 (24GB)llama.cpp@0.7.0-dev (build 1, commit ea0c4c2)chat-short42.7236.9472.7r_qm1xyvjmx_r
Flint-40B-A2.5B-UD-cpumoe6-ctx8kQ4_K_XLRTX 4090 (24GB) + AMD EPYC 7452 32-Core Processor (32c) + 504GBllama.cpp@0.7.0-dev (build 11803, commit a37cc4610)concurrent-decode42.7——r_wap61ewkpzm
Qwen3.8-27B-ctx8kQ4_K_MRTX 3090 (24GB)llama.cpp@0.7.0-dev (build 11803, commit a37cc4610)chat-short38.8479.1321.5r_w40_vv7f77w
Qwen3.8-27B-ctx4kQ4_K_MRTX 3090 (24GB)llama.cpp@0.7.0-dev (build 11803, commit a37cc4610)chat-short38.6482.3319.3r_mmtzel_i367
Qwen3.8-27B-ctx16kQ4_K_MRTX 3090 (24GB)llama.cpp@0.7.0-dev (build 11803, commit a37cc4610)chat-short38.6482.7319.0r_gscy1f7ey_k
Qwen3-32BQ4_K_MRTX 3090 (24GB)llama.cpp@0.7.0-dev (build 1, commit ea0c4c2)chat-short38.5589.5186.6r_km62sybxga6
Qwen3.8-27BQ4_K_MRTX 3090 (24GB)llama.cpp@0.6.0-dev (build 1, commit 8c2134a)chat-short37.6368.5417.9r_ptct8o01o5l
mlx-community-Qwen2.5-32B-Instruct-4bit4bitM3 Ultra (60-core GPU) + 96GB unifiedmlx@0.31.3chat-short34.6141.9922.9r_njgxtgyym1e
mlx-community/Qwen2.5-Coder-32B-Instruct-4bit-M3 Ultra (60-core GPU) + 96GB unifiedmlx@0.31.3chat-short34.5144.1909.4r_721b4bls_oq
mlx-community/Qwen3-32B-4bit-M3 Ultra (60-core GPU) + 96GB unifiedmlx@0.31.3chat-short34.495.11156.4r_anmmc80-aoq
mlx-community-Qwen2.5-7B-Instruct-4bit4bitM3 Pro (18-core GPU) + 36GB unifiedmlx@0.31.3chat-short30.5161.9809.1r_llzv_g-ymaf
mlx-community/Llama-3.1-8B-Instruct-4bit-M3 Pro (18-core GPU) + 36GB unifiedmlx@0.31.3chat-short29.2203.3669.0r_h0-use1ypnb
Muse-Spark-Open-816B-A42B-UD-00001-of-00005IQ1_S3x A100 (80GB)llama.cpp@0.7.0-dev (build 11675, commit 2851b3bcb)concurrent-decode26.3——r_fsd9qjmmna0
llama3.2Q8_0AMD64 Family 23 Model 104 Stepping 1, AuthenticAMD (6c) + 15GBollama@0.34.0chat-short23.939.43171.6r_b1rn5gi6b3b
Muse-Glimmer-30B-ctx8kUD-IQ3_XXSRTX A4000 (16GB)llama.cpp@0.7.0-dev (build 11803, commit a37cc4610)chat-short23.3265.1580.8r_u_kr0v-wwde
mlx-community/gemma-2-9b-it-4bit-M3 Pro (18-core GPU) + 36GB unifiedmlx@0.31.3chat-short22.0102.51151.3r_q7t7b7dcuz5
Muse-Glimmer-30B-ctx128kUD-IQ3_XXSRTX A4000 (16GB)llama.cpp@0.7.0-dev (build 11803, commit a37cc4610)chat-short21.9255.0603.9r_1lyb_mqmdik
Muse-Glimmer-30B-ctx96k-kvq8UD-IQ3_XXSRTX A4000 (16GB)llama.cpp@0.7.0-dev (build 11803, commit a37cc4610)chat-short21.8264.1583.1r_0o1xfrrn-ch
Muse-Glimmer-30B-ctx48k-kvq8UD-IQ3_XXSRTX A4000 (16GB)llama.cpp@0.7.0-dev (build 11803, commit a37cc4610)chat-short21.7273.7562.7r_x8mqtlf166j
Muse-Glimmer-30B-ctx16k-kvq8UD-IQ3_XXSRTX A4000 (16GB)llama.cpp@0.7.0-dev (build 11803, commit a37cc4610)chat-short21.7253.3607.9r_dldd3d54262
Muse-Glimmer-30B-ctx8k-kvq8UD-IQ3_XXSRTX A4000 (16GB)llama.cpp@0.7.0-dev (build 11803, commit a37cc4610)chat-short21.7271.4567.4r_b8y4oh7e0-z
Muse-Glimmer-30B-ctx128k-kvq8UD-IQ3_XXSRTX A4000 (16GB)llama.cpp@0.7.0-dev (build 11803, commit a37cc4610)chat-short21.7246.1625.8r_crqe50ubylk
Muse-Glimmer-30B-ctx32k-kvq8UD-IQ3_XXSRTX A4000 (16GB)llama.cpp@0.7.0-dev (build 11803, commit a37cc4610)chat-short21.6272.3565.6r_zoeatakzums
Muse-Glimmer-30B-ctx96kUD-IQ3_XXSRTX A4000 (16GB)llama.cpp@0.7.0-dev (build 11803, commit a37cc4610)chat-short21.6265.7579.7r_pf4ye8_4xmc
Muse-Glimmer-30B-ctx64k-kvq8UD-IQ3_XXSRTX A4000 (16GB)llama.cpp@0.7.0-dev (build 11803, commit a37cc4610)chat-short21.5266.6577.7r_aufjud7duqr
Muse-Glimmer-30B-ctx64kUD-IQ3_XXSRTX A4000 (16GB)llama.cpp@0.7.0-dev (build 11803, commit a37cc4610)chat-short21.5274.6560.8r_j9yaui8ovvy
Muse-Glimmer-30B-ctx32kUD-IQ3_XXSRTX A4000 (16GB)llama.cpp@0.7.0-dev (build 11803, commit a37cc4610)chat-short21.5269.7571.0r_ntsos2cxwja
Muse-Glimmer-30B-ctx48kUD-IQ3_XXSRTX A4000 (16GB)llama.cpp@0.7.0-dev (build 11803, commit a37cc4610)chat-short21.5271.6566.9r_y8qy4yd5p7i
Muse-Glimmer-30B-ctx16kUD-IQ3_XXSRTX A4000 (16GB)llama.cpp@0.7.0-dev (build 11803, commit a37cc4610)chat-short21.4256.7600.0r_y9y09s77lfa
Llama-3.3-70B-InstructQ4_K_M2x RTX 3090 (24GB)llama.cpp@0.7.0-dev (build 1, commit f74e2fa)chat-short19.1415.4325.0r_n93ukk0mkmm
Flint-40B-A2.5B-UD-cpumoe6-ctx8kQ4_K_XLRTX 3090 (24GB) + AMD EPYC 7763 64-Core Processor (128c) + 1008GBllama.cpp@0.7.0-dev (build 11803, commit a37cc4610)chat-long17.41316.22290.0r_klxxsjjp2m-
mlx-community/llama-3.3-70b-Instruct-4bit-M3 Ultra (60-core GPU) + 96GB unifiedmlx@0.31.3chat-short16.825.15419.9r_sx3a4y9n-m4
mlx-community/qwen2.5-72b-Instruct-4bit-M3 Ultra (60-core GPU) + 96GB unifiedmlx@0.31.3chat-short16.323.25635.3r_5c80gthqlh6
Flint-40B-A2.5B-UD-cpumoe12-ctx8kQ3_K_XLRTX A4000 (16GB) + AMD EPYC 7453 28-Core Processor (56c) + 504GBllama.cpp@0.7.0-dev (build 11803, commit a37cc4610)chat-short15.7190.0515.8r_acy-a8qic5j
mlx-community/phi-4-4bit-M3 Pro (18-core GPU) + 36GB unifiedmlx@0.31.3chat-short15.6120.7936.0r_-w8hnn61va_
mlx-community-Qwen2.5-14B-Instruct-4bit4bitM3 Pro (18-core GPU) + 36GB unifiedmlx@0.31.3chat-short14.4117.91111.5r_ia73dzeue0b
Llama-3.3-70B-InstructQ4_K_MA40 (45GB)llama.cpp@0.7.0-dev (build 1, commit ceefd16)chat-short13.0401.0336.7r_19f64yux97o
mlx-community/Qwen3-32B-4bit-M3 Pro (18-core GPU) + 36GB unifiedmlx@0.31.3chat-short7.225.74287.9r_pnrrpcdqfo4
mlx-community/Qwen2.5-32B-Instruct-4bit-M3 Pro (18-core GPU) + 36GB unifiedmlx@0.31.3chat-short7.133.43921.1r_f4x3xaan2ay

A40 (45GB): 48GB, ~45 GiB usable. The label shows what its driver reports as usable, not the 48GB spec.

How to read this table

Each row is the highest decode tokens-per-second measured for a unique (model, hardware) pair. When more than one workload was run, we pick the workload that produced the headline number. Lower-tps duplicates from the same machine are not shown; click through to the run page for the full per-workload breakdown.

decode tok/s is wall-clock streaming throughput (memory-bandwidth-bound). prefill tok/s is prompt ingestion throughput (compute-bound). TTFT is time-to-first-token in milliseconds. See /glossary for definitions and /methodology for the workload spec.