[whatmodel.sh](../../README.md) / Qwen3.5 122B-A10B
# Qwen3.5 122B-A10B
Alibaba · released 2026-02 · 125B params (10B active) · apache-2.0
**score 67.8** ±0.5 · #102 of 732 · from 89 benchmark results across 11 sources
Score within the [LMArena (text)](https://whatmodel.sh/?set=lmarena-text&score=set) comparison set only.
## What it's good at
● marks Qwen3.5 122B-A10B among every model on that task or test, worst to best.
task vs the others rank counts tests
agent tasks ▁▁▃▆█▄▅●▄▄▂▁ #89 of 313 17% 10
coding ▁▁▁▃▅▇█▇●▄▃▁ #112 of 469 13% 3
chat & writing ▁▁▁▃▆▄▆█▆●▇▃ #95 of 402* 3.7% 2
math ▁▁▃▅█▆▄●▄▂▁▁ #91 of 431 7.7% 6
vision & documents ▁▁▂▂▁▃▄▂▆●█▄ #60 of 153 15% 19
web search ▁▁▁●▄█▃▄·▁·▁ #62 of 84 5.2% 5
agent tasks · #89 of 313 · 17% of its score
Beats [Grok 4.20 (0309 reasoning)](grok-4-20.md), [GPT-5.1](gpt-5-1.md), [o3-pro](o3-pro.md) here, though they rank higher overall. Trails [MiniMax-M2.7](minimax-m2-7.md), [Step 3.5 Flash (196B-A11B)](step-3-5-flash.md), [Nemotron 3.5 Bolt 74B A9B](nemotron-3-5-bolt-74b-a9b.md) here, though they rank lower overall.
test result vs the others in its run difficulty counts why
SWE-bench Verified (maker) 72.0% ▁▁▁▁▁▁▂▄●▆▁▁ beats 89/138 hard · avg 23% 4.8% sharp · at its level · small run · seve…
τ²-bench aggregate (maker) 79.5% ▁▁▁·▁▁▃▃▃●█▁ beats 23/39 medium · avg 41% 2.5% several runs
Terminal-Bench 2.0 (maker) 49.4% ▂▂▅▅██●█▆▂▃▃ beats 19/36 very hard · avg 11% 1.8% at its level · small run
OSWorld-Verified (maker) 58.0% █▃·▂●▂▃▂▅▃▆▆ beats 9/27 hard · avg 20% 1.6% at its level · small run
BrowseComp-ZH (maker) 69.9% ▁▁▁▁▁▃·▁▄▅▄● beats 21/23 hard · avg 25% 1.4% at its level · small run
BrowseComp (maker) 63.8% ▂·▃▁▂▂▆▅●▂▂▄ beats 31/46 hard · avg 27% 1.1% at its level · small run
Humanity's Last Exam with tools (… 47.5% ▁·▁▂▂▁▄▄●█▄▅ beats 29/62 hard · avg 18% 1.1% at its level · small run
EEGAgentBench overall (tool-based… 48.5% ▂·▁▁··▇●█▂·▁ beats 15/25 hard · avg 28% 0.9% blunt · at its level
WideSearch (maker) 60.5% ●·▂▆··▂···▂▂ beats 3/10 hard · avg 33% 0.8% at its level · small run
BFCL V4 (December 2025 archive) (… 72.2% ▁▁▁▂▆▆▅▆█▂▄● beats 109/114 medium · avg 41% 0.8% at its level · small run
coding · #112 of 469 · 13% of its score
Beats [Grok 4.3](grok-4-3.md), [Muse Glimmer 30B](muse-glimmer-30b.md), [Qwen3.5 Plus](qwen3-5-plus.md) here, though they rank higher overall. Trails [Llama 3.1 Nemotron Ultra 253B v1](llama-3-1-nemotron-ultra-253b.md), [Solar Pro 4](solar-pro-4.md), [Nemotron Cascade 2 30B-A3B](nemotron-cascade-2-30b-a3b.md) here, though they rank lower overall.
test result vs the others in its run difficulty counts why
Arena WebDev (Code Arena) 1360.4 ▁▁▃▂●█▃▆▅▅▁▂ beats 33/129 avg 981 5.4% sharp
SWE-bench Verified (maker) 72.0% ▁▁▁▁▁▁▂▄●▆▁▁ beats 89/138 hard · avg 23% 4.8% sharp · at its level · small run · seve…
LiveCodeBench v6 (Feb–May 2025) (… 78.9% ▁▁▃▁█▅▄▇▅●▃█ beats 29/38 medium · avg 44% 2.6% several runs
chat & writing · #95 of 402 · 3.7% of its score
Beats [LongCat 2.0 (1.6T-A48B)](longcat-2-0.md), [Inkling Small (266B-A12B)](inkling-small.md) here, though they rank higher overall. Trails [Gemma 4 12B](gemma-4-12b.md), [Kimi K2 Instruct (0905)](kimi-k2-0905.md), [Gemma 4 26B-A4B](gemma-4-26b-a4b.md) here, though they rank lower overall.
test result vs the others in its run difficulty counts why
LMArena (text) 1416.5 ▁▁▁▂▃▃▃▆▆●█▃ beats 269/385 avg 1260 3.1% blunt
IFEval (aggregation unspecified) … 93.4% ▁▂▄▂▂▄▆██●▂▁ beats 134/145 easy · avg 81% 0.7% maxed out · small run
math · #91 of 431 · 7.7% of its score
Beats [Claude Sonnet 4.6](claude-sonnet-4-6.md), [Claude Opus 4.5](claude-opus-4-5.md), [MiniMax-M3](minimax-m3.md) here, though they rank higher overall. Trails [Gemini 2.5 Flash](gemini-2-5-flash.md), [Granite 4.2 30B](granite-4-2-30b.md), [Qwen3-Next 80B-A3B Instruct](qwen3-next-80b-a3b-instruct.md) here, though they rank lower overall.
test result vs the others in its run difficulty counts why
MATH-Vision (maker) 86.2% ▁▁·▁··▄▁▃▇▇● beats 22/24 medium · avg 55% 2.2% small run · several runs
HMMT February 2025 (maker) 91.4% ▁▁▁▃▁▅▅▃●█▁▄ beats 20/31 medium · avg 63% 1.6% small run
MathVista (testmini) (maker) 87.4% ▁··▁▄▄▆▇▄▅█● beats 46/48 medium · avg 64% 1.1% small run
HMMT November 2025 (maker) 90.3% ▁▁····▁▅▃●▇▁ beats 14/23 easy · avg 69% 1.0% small run
PolyMATH (maker) 68.9% ▁···▃▁·▇█▄▄● beats 21/23 medium · avg 35% 1.0% at its level · small run
DynaMath (maker) 85.9% ▂·····▂··█▄● beats 8/10 easy · avg 66% 0.8% small run
vision & documents · #60 of 153 · 15% of its score
Beats [GPT-6 Luna](gpt-6-luna.md), [DeepSeek V4 Flash Vision (Exp)](deepseek-v4-flash-vision-exp.md), [GPT-5](gpt-5.md) here, though they rank higher overall. Trails [Gemma 4 26B-A4B](gemma-4-26b-a4b.md), [Qwen3.6 Flash](qwen3-6-flash.md), [Qwen3.5 35B-A3B](qwen3-5-35b-a3b.md) here, though they rank lower overall.
test result vs the others in its run difficulty counts why
MATH-Vision (maker) 86.2% ▁▁·▁··▄▁▃▇▇● beats 22/24 medium · avg 55% 2.2% small run · several runs
Arena vision (style controlled) 1226.2 ▁▁▂▂▂▂▃▄▅●█▇ beats 88/152 avg 1061 2.0% blunt
CharXiv (reasoning questions) (ma… 77.2% ▂▅▃▅▅▆▆▅●█▆▂ beats 67/101 medium · avg 43% 1.3% small run
MathVista (testmini) (maker) 87.4% ▁··▁▄▄▆▇▄▅█● beats 46/48 medium · avg 64% 1.1% small run
MMMU (val) (maker) 83.9% ▁····▁▁▃█▆▆● beats 52/53 medium · avg 58% 1.1% small run
MMMU Pro (maker) 76.9% ▂▃▁▃▆▇▃▇▇█●▅ beats 44/52 medium · avg 47% 1.1% at its level · small run
OmniDocBench 1.5 overall (higher … 89.8% ▂··▂▂▂··▂▂●▅ beats 9/13 easy · avg 71% 0.8% small run
MMStar (maker) 82.9% ▃▅▂▃▂▂▆██▆█● beats 34/35 medium · avg 63% 0.8% small run
CountBench (maker) 97.0% ▂▂▃▂·▂▂▃▃·●█ beats 13/18 very easy · avg 92% 0.6% maxed out · small run
PMC-VQA (maker) 63.3% ▃···▃··▃▃·▃● beats 6/7 medium · avg 39% 0.6% at its level · small run
SimpleVQA (maker) 61.7% ▃·▃·▃·▃·█▅●▃ beats 9/10 hard · avg 35% 0.6% blunt · at its level · small run
MMBench-EN dev v1.1 (maker) 92.8% █▄···▂··▄▂▄● beats 13/14 easy · avg 82% 0.5% blunt · maxed out · small run
ScreenSpot-Pro (maker) 70.4% ▂▃▅▆█●▅▂···▂ beats 19/24 medium · avg 48% 0.5% blunt · at its level · small run
HallusionBench (maker) 67.6% ▂▁·▂▂▂▃▅▃█●▅ beats 28/33 medium · avg 53% 0.4% blunt · at its level · small run
RealWorldQA (maker) 85.1% ▁▃▁▇▃▇▇▅█▁▅● beats 36/39 easy · avg 72% 0.3% blunt · small run
CC-OCR (maker) 81.8% ▁·▂··▂▂▃▃▂▆● beats 23/26 easy · avg 71% 0.3% blunt · small run
OCRBench (maker) 92.1% ▁·▃▁▆▅▂█▅█▁● beats 36/37 easy · avg 83% 0.2% blunt · small run
AI2D test (maker) 93.3% ▁▁▅▇▃▇·▄·●·▃ beats 25/28 easy · avg 86% 0.2% blunt · small run
PureDocBench document parsing (Av… 74.1% ▂·▁·▂▂▅█·●▂▂ beats 18/22 medium · avg 62% 0.1% blunt · at its level
web search · #62 of 84 · 5.2% of its score
Beats [DeepSeek V4 Flash (Preview, Apr 2026)](deepseek-v4-flash-preview.md), [GPT-5.4 mini](gpt-5-4-mini.md), [Qwen3.5 397B-A17B](qwen3-5-397b-a17b.md) here, though they rank higher overall. Trails [GPT-4o mini (2024-07-18)](gpt-4o-mini-2024-07-18.md), [Mistral Small 3.1 24B (2503)](mistral-small-3-1.md), [Llama 4 Scout (109B-A17B)](llama-4-scout.md) here, though they rank lower overall.
test result vs the others in its run difficulty counts why
BrowseComp-ZH (maker) 69.9% ▁▁▁▁▁▃·▁▄▅▄● beats 21/23 hard · avg 25% 1.4% at its level · small run
BrowseComp (maker) 63.8% ▂·▃▁▂▂▆▅●▂▂▄ beats 31/46 hard · avg 27% 1.1% at its level · small run
Humanity's Last Exam with tools (… 47.5% ▁·▁▂▂▁▄▄●█▄▅ beats 29/62 hard · avg 18% 1.1% at its level · small run
WideSearch (maker) 60.5% ●·▂▆··▂···▂▂ beats 3/10 hard · avg 33% 0.8% at its level · small run
SealQA Seal-0 (maker) 44.1% █····●·····█ beats 1/2 hard · avg 20% 0.7% at its level · small run
other tests (44)
test result vs the others in its run difficulty counts why
GPQA Diamond (maker) 86.6% ▁▁▁▁▂▄▅▅██●▄ beats 246/322 hard · avg 43% 7.5% sharp · several runs
Humanity's Last Exam (maker) 25.3% ▁▁▁▄▆▆▇●█▆▁▃ beats 64/111 very hard · avg 5.1% 3.8% several runs
MMLU-Pro (maker) 86.7% ▁▁·▁▁▁▃▂▄▅█● beats 183/188 medium · avg 57% 3.2% several runs
KINA (Knowledge Index of Noah's A… 38.9% ▁▁▂▁▃▄█▆▄●▂▃ beats 31/39 very hard · avg 21% 2.3% at its level
MedXPertQA MM (maker) 67.3% ▂···▂·▃··▆▂● beats 12/13 very hard · avg 31% 2.1% sharp · at its level · small run
Mystery Game Puzzles (Epoch) 17.0% █··▂▃●▄█▂▄▂▁ beats 27/77 very hard · avg 9.4% 1.8% sharp · too hard for it · noisy
Polish medical board exams, bias-… 75.1% ▄·▂▂▂··█▂▄·● beats 13/13 hard · avg 46% 1.8% at its level
LongBench v2 (maker) 60.2% ▂·▁·▂▃▁▄▄▃●▄ beats 24/33 very hard · avg 35% 1.7% at its level · small run
C-Eval (maker) 91.9% ▁···▁▁▂▁▂▂▃● beats 30/33 medium · avg 71% 1.3% small run
INCLUDE (maker) 82.8% ▂····▂▂▄▄▄█● beats 34/36 medium · avg 55% 1.3% small run
MMLU-Redux (maker) 94.0% ▁▁▃▁▂▃▄▅▇▅█● beats 61/63 easy · avg 78% 1.2% maxed out · small run
MMMLU (maker) 86.7% ▂▁▁▂▃▂▄▄▅█●▃ beats 40/46 medium · avg 63% 1.2% small run
CPTUB average (SpeakLeash, 0-5 ju… 87.3% ▁▂▂▂▃█▃▆▅▄▂● beats 93/95 medium · avg 65% 1.2% typical
OJBench (maker) 39.5% ▁···▁▃·▅▄▅█● beats 23/26 very hard · avg 13% 1.2% at its level · small run
VitaBench (maker) 33.6% ▄··▂▄▆▆█●▄▄▂ beats 16/21 very hard · avg 11% 1.1% at its level · small run
IFBench (aggregation unspecified)… 76.1% ▂▆▂▄▄▄▂▄▄▆●▇ beats 71/86 medium · avg 43% 0.9% at its level · small run
Global PIQA (maker) 88.4% ▃▃··▃··▃▃▅█● beats 10/11 medium · avg 73% 0.9% small run
MultiChallenge (maker) 61.5% ▁·▁·▁▃▆▅▃▂●▅ beats 23/30 hard · avg 31% 0.9% at its level · small run
SuperGPQA (maker) 67.1% ▂▁▂▂▅▆▃▇▇▇█● beats 44/46 medium · avg 37% 0.9% at its level · small run
MAXIFE (maker) 87.9% ▂·▂·▂···▆·▄● beats 9/11 easy · avg 67% 0.8% small run
MMLU-ProX (maker) 82.2% ▁·▁▁▁▂▁▃▃█●▄ beats 29/36 medium · avg 58% 0.8% small run
VideoMMMU (maker) 82.0% ▂···▂···▂▂●▆ beats 6/10 medium · avg 60% 0.8% small run
VLMs Are Blind (maker) 96.7% ▂·▂·····▃··● beats 5/8 very easy · avg 90% 0.8% maxed out · small run
LVBench (maker) 74.4% ▇·█▅▅▄●··▃▁▁ beats 23/28 medium · avg 53% 0.7% at its level · small run
LingoQA (maker) 80.8% ▄······▄·●·█ beats 3/5 medium · avg 58% 0.7% small run
SLAKE (maker) 81.6% ▄·····▄▄·██● beats 7/7 medium · avg 60% 0.7% small run
Video-MME (with subtitles) (maker) 87.3% ▁▁▁▁▁·▁▃▁▁▁● beats 14/16 medium · avg 71% 0.7% small run
DeepPlanning (maker) 24.1% ▂·····▂··▄●▄ beats 6/9 very hard · avg 9.2% 0.7% small run
MMVU (maker) 74.7% ▃···▃···▃▃▅● beats 7/8 medium · avg 49% 0.7% at its level · small run
FullStackBench (Chinese) (maker) 58.7% █······█···● beats 2/2 hard · avg 30% 0.7% at its level · small run
FullStackBench (English) (maker) 62.6% █····█·····● beats 2/2 hard · avg 33% 0.7% at its level · small run
RefSpatial-Bench (maker) 69.3% ▃·▃····▃▃▅●█ beats 7/10 medium · avg 41% 0.7% at its level · small run
ZEROBench subquestions (maker) 36.2% ▄·▄···▄·▄█●▄ beats 7/8 hard · avg 17% 0.7% at its level · small run
MLVU (maker) 87.3% ▂···▂···▂▄▄● beats 10/10 easy · avg 69% 0.7% small run
MMLongBench-Doc (maker) 59.0% ▃···▃···▃▅●▅ beats 5/9 medium · avg 36% 0.7% at its level · small run
ERQA (maker) 62.0% ▃··▃··█·▃●▅▅ beats 7/12 medium · avg 37% 0.7% at its level · small run
EmbSpatial-Bench (maker) 83.9% ▁·····▁·▁·▃● beats 5/10 easy · avg 67% 0.6% small run
AndroidWorld (maker) 66.4% ▁·▁▁▂▃█▅●▂·▂ beats 19/24 medium · avg 42% 0.6% at its level · small run
NOVA-63 (maker) 58.6% ▃▃·▃···▃█▃▃● beats 10/11 medium · avg 36% 0.6% blunt · at its level · small run
Video-MME (without subtitles) (ma… 83.9% ▁▃▁▃▁·█▄▄▅·● beats 27/27 medium · avg 68% 0.5% blunt · small run
MVBench (maker) 76.6% ▁··▃▄▁▃▄▄▄█● beats 25/26 medium · avg 65% 0.3% blunt · at its level · small run
LIBRA Mini (Russian long context,… 42.7% ▄···▄█·●█··▄ beats 5/8 medium · avg 38% 0.2% blunt · at its level
WMT24++ (maker) 78.3% ▁·▁▁·▁·▁▂▆●▃ beats 16/27 easy · avg 68% 0.1% blunt · small run
Vectara hallucination leaderboard… 88.8% ▁▂▁▂●█▂▃▄▃▁▁ beats 31/98 very easy · avg 90% 0.0% blunt
source results share of the score
Qwen/Qwen3.5-122B-A10B model card (subm… 71 67% ▇▇▇▇▇▇▇▇
Qwen/Qwen3.5-27B model card (submitted … 7 14% ▇▇
LMArena leaderboard dataset 3 11% ▇
Knowledge Index of Noah's Ark 1 2% ▇
Epoch AI 1 2% ▇
Reassessing High-Performing LLMs on Pol… 1 2% ▇
SpeakLeash CPTUB 1 1% ▇
EEGAgentBench: Benchmarking LLM Agents … 1 1% ▇
ai-forever LIBRA leaderboard 1 0% ▇
How Far Is Document Parsing from Solved… 1 0% ▇
Vectara hallucination leaderboard 1 0% ▇
prior: pull toward the middle 0% ▇
weighted average = 67.8
Licences: Qwen/Qwen3.5-122B-A10B model card ([apache-2.0](../../licenses/Qwen--Qwen3.5-122B-A10B.txt)) · Qwen/Qwen3.5-27B model card ([apache-2.0](../../licenses/Qwen--Qwen3.5-27B.txt)) · LMArena leaderboard dataset ([CC BY 4.0](https://creativecommons.org/licenses/by/4.0/)) · Knowledge Index of Noah's Ark ([CC BY 4.0](https://creativecommons.org/licenses/by/4.0/)) · Epoch AI ([CC BY 4.0](https://creativecommons.org/licenses/by/4.0/)) · Reassessing High-Performing LLMs on Polish Medical Exams: True Competence or Bias-Driven Performance? ([CC BY-SA 4.0](https://creativecommons.org/licenses/by-sa/4.0/)) · SpeakLeash CPTUB ([MIT](../../licenses/hf-leaderboard-spaces-MIT.txt)) · EEGAgentBench: Benchmarking LLM Agents on Short- and Long-Horizon EEG Analysis ([CC BY 4.0](https://creativecommons.org/licenses/by/4.0/)) · ai-forever LIBRA leaderboard ([MIT](../../licenses/hf-leaderboard-spaces-MIT.txt)) · How Far Is Document Parsing from Solved? PureDocBench: A Source-Traceable Benchmark across Clean ([CC BY 4.0](https://creativecommons.org/licenses/by/4.0/)) · Vectara hallucination leaderboard ([Apache-2.0](https://www.apache.org/licenses/LICENSE-2.0))
## How to run it
### Through an API
api (Alibaba Cloud Model Studio) · $1.10/M blended · $0.4 in / $3.2 out per 1M tokens · [alibabacloud.com](https://www.alibabacloud.com/help/en/model-studio/models)
[price source](https://www.alibabacloud.com/help/en/model-studio/model-pricing): USD per 1M tokens, Singapore (International), qwen3.5-122b-a10b, 0\
### llama.cpp (recommended)
1. Install llama.cpp. Homebrew and winget installs name the commands llama-cli and llama-server instead. [Other ways to install](https://github.com/ggml-org/llama.cpp/blob/master/docs/install.md)
```sh
# macOS / Linux
curl -LsSf https://llama.app/install.sh | sh
# Windows
irm https://llama.app/install.ps1 | iex
```
2. Run Qwen3.5 122B-A10B (Q4_K_M, needs ~74.2 GB, from [huggingface.co/lmstudio-community](https://huggingface.co/lmstudio-community/Qwen3.5-122B-A10B-GGUF/tree/a5ba02062d2fd26c1f17000571ffc86e7abf4c92))
```sh
llama cli -hf lmstudio-community/Qwen3.5-122B-A10B-GGUF:Q4_K_M
```
3. Or start a local server and open the address it prints (http://localhost:9931)
```sh
llama serve -hf lmstudio-community/Qwen3.5-122B-A10B-GGUF:Q4_K_M
```
Other versions: Q8_0 (~129.9 GB) `llama cli -hf lmstudio-community/Qwen3.5-122B-A10B-GGUF:Q8_0`
### LM Studio
1. Install LM Studio. Open the app once before using the lms command. [Download it (macOS / Windows / Linux)](https://lmstudio.ai/download)
2. Run Qwen3.5 122B-A10B (Q4_K_M, needs ~74.2 GB, from [huggingface.co/lmstudio-community](https://huggingface.co/lmstudio-community/Qwen3.5-122B-A10B-GGUF/tree/a5ba02062d2fd26c1f17000571ffc86e7abf4c92))
```sh
lms get https://huggingface.co/lmstudio-community/Qwen3.5-122B-A10B-GGUF@Q4_K_M -y
```
3. Then run lms ls to see its name, and lms chat followed by that name
Other versions: Q8_0 (~129.9 GB) `lms get https://huggingface.co/lmstudio-community/Qwen3.5-122B-A10B-GGUF@Q8_0 -y` · 4bit (~69.6 GB, Mac only) `lms get https://huggingface.co/mlx-community/Qwen3.5-122B-A10B-4bit -y` · 8bit (~130.6 GB, Mac only) `lms get https://huggingface.co/mlx-community/Qwen3.5-122B-A10B-8bit -y`
### Ollama
1. Install Ollama. [Download it (macOS / Windows)](https://ollama.com/download)
```sh
# Linux
curl -fsSL https://ollama.com/install.sh | sh
```
2. Run Qwen3.5 122B-A10B (Q4_K_M, needs ~75.5 GB, from [ollama.com](https://ollama.com/library/qwen3.5/tags))
```sh
ollama run qwen3.5:122b
```
### MLX (Mac)
1. Install MLX (Mac). Apple silicon Macs only, text only.
```sh
# with uv
uv tool install mlx-lm
# or
pip install mlx-lm
```
2. Run Qwen3.5 122B-A10B (4bit, needs ~69.6 GB, Mac only, from [huggingface.co/mlx-community](https://huggingface.co/mlx-community/Qwen3.5-122B-A10B-4bit/tree/e9c67b08899964be5fdd069bb1b4bc8907fe68f5))
```sh
mlx_lm.chat --model mlx-community/Qwen3.5-122B-A10B-4bit
```
3. Or start an OpenAI-compatible server at http://localhost:8080/v1
```sh
mlx_lm.server --model mlx-community/Qwen3.5-122B-A10B-4bit
```
Other versions: 8bit (~130.6 GB, Mac only) `mlx_lm.chat --model mlx-community/Qwen3.5-122B-A10B-8bit`
Model repository and documentation: [huggingface.co/Qwen](https://huggingface.co/Qwen/Qwen3.5-122B-A10B)
## Quantization evidence
How much of the full-precision result a quantized version kept, measured within one study. Rows from the same study share a table and aren't independent. They don't describe every download of that precision.
precision test full → quantized kept
FP8 W8A8 dynamic (E4M3; weigh… LiveCodeBench v6 code generation … 0.813 → 0.819 100.7%
FP8 W8A8 dynamic (E4M3; weigh… AIME 2025 0-shot (lighteval via l… 0.921 → 0.925 100.5%
FP8 W8A8 dynamic (E4M3; weigh… GSM8K-Platinum 0-shot (lm-evaluat… 0.956 → 0.957 100.1%
FP8 W8A8 dynamic (E4M3; weigh… MMLU-Pro 0-shot (lm-evaluation-ha… 0.87 → 0.87 100.0%
FP8 W8A8 dynamic (E4M3; weigh… MATH-500 0-shot (lighteval via li… 0.852 → 0.851 99.9%
FP8 W8A8 dynamic (E4M3; weigh… IFEval prompt-level strict 0-shot… 0.921 → 0.911 99.0%
FP8 W8A8 dynamic (E4M3; weigh… GPQA Diamond 0-shot (lighteval vi… 0.874 → 0.86 98.5%
Each kept value links to its source.
[interactive version](https://whatmodel.sh/model/qwen3-5-122b-a10b) · [JSON](https://whatmodel.sh/api?format=json&all=1)