GPT-OSS 120B vs Qwen3.5-122B-A10B

Side-by-side benchmark comparison across agentic, coding, multimodal, knowledge, reasoning, and math workflows.

Agentic
Coding
Multimodal & Grounded
Reasoning
Knowledge
Instruction Following
Multilingual
Mathematics

GPT-OSS 120B· Qwen3.5-122B-A10B

Quick Verdict

Pick Qwen3.5-122B-A10B if you want the stronger benchmark profile. GPT-OSS 120B only becomes the better choice if you would rather avoid the extra latency and token burn of a reasoning model.

Qwen3.5-122B-A10B is clearly ahead on the aggregate, 71 to 51. The gap is large enough that you do not need to squint at the spreadsheet to see the difference.

Qwen3.5-122B-A10B's sharpest advantage is in coding, where it averages 76.3 against 30. The single biggest benchmark swing on the page is LiveCodeBench, 25% to 78.9%.

Qwen3.5-122B-A10B is the reasoning model in the pair, while GPT-OSS 120B is not. That usually helps on harder chain-of-thought-heavy tests, but it can also mean more latency and more token spend in real use. Qwen3.5-122B-A10B gives you the larger context window at 262K, compared with 128K for GPT-OSS 120B.

Operational tradeoffs

PriceFree*Free*
Speed262 t/sN/A
TTFT0.79sN/A
Context128K262K

Decision framing

BenchLM keeps the benchmark table and the operator tradeoffs on the same page so a better score does not hide a materially slower, pricier, or smaller-context model.

Runtime metrics show N/A when BenchLM does not have a sourced snapshot for that exact model. The scoring rules and freshness policy are documented on the methodology page.

BenchmarkGPT-OSS 120BQwen3.5-122B-A10B
AgenticQwen3.5-122B-A10B wins
Terminal-Bench 2.043%49.4%
BrowseComp50%63.8%
OSWorld-Verified43%58%
tau2-bench79.5%
CodingQwen3.5-122B-A10B wins
HumanEval43%
SWE-bench Verified29%72%
LiveCodeBench25%78.9%
SWE-bench Pro31%
SWE-Rebench33.3%
React Native Evals66.4%
Multimodal & GroundedQwen3.5-122B-A10B wins
MMMU-Pro42%76.9%
OfficeQA Pro57%
ReasoningQwen3.5-122B-A10B wins
MuSR47%
BBH73%
LongBench v258%60.2%
MRCRv259%
KnowledgeQwen3.5-122B-A10B wins
MMLU90%
GPQA80.9%86.6%
SuperGPQA48%67.1%
MMLU-Pro90%86.7%
HLE5%
FrontierScience49%
SimpleQA49%
Instruction FollowingQwen3.5-122B-A10B wins
IFEval79%93.4%
MultilingualQwen3.5-122B-A10B wins
MGSM72%
MMLU-ProX70%82.2%
Mathematics
AIME 202351%
AIME 202453%
AIME 202552%
HMMT Feb 202347%
HMMT Feb 202449%
HMMT Feb 202548%
BRUMO 202550%
MATH-50071%
Frequently Asked Questions (8)

Which is better, GPT-OSS 120B or Qwen3.5-122B-A10B?

Qwen3.5-122B-A10B is ahead overall, 71 to 51. The biggest single separator in this matchup is LiveCodeBench, where the scores are 25% and 78.9%.

Which is better for knowledge tasks, GPT-OSS 120B or Qwen3.5-122B-A10B?

Qwen3.5-122B-A10B has the edge for knowledge tasks in this comparison, averaging 81.6 versus 51.6. Inside this category, SuperGPQA is the benchmark that creates the most daylight between them.

Which is better for coding, GPT-OSS 120B or Qwen3.5-122B-A10B?

Qwen3.5-122B-A10B has the edge for coding in this comparison, averaging 76.3 versus 30. Inside this category, LiveCodeBench is the benchmark that creates the most daylight between them.

Which is better for reasoning, GPT-OSS 120B or Qwen3.5-122B-A10B?

Qwen3.5-122B-A10B has the edge for reasoning in this comparison, averaging 60.2 versus 55.4. Inside this category, LongBench v2 is the benchmark that creates the most daylight between them.

Which is better for agentic tasks, GPT-OSS 120B or Qwen3.5-122B-A10B?

Qwen3.5-122B-A10B has the edge for agentic tasks in this comparison, averaging 56 versus 44.8. Inside this category, OSWorld-Verified is the benchmark that creates the most daylight between them.

Which is better for multimodal and grounded tasks, GPT-OSS 120B or Qwen3.5-122B-A10B?

Qwen3.5-122B-A10B has the edge for multimodal and grounded tasks in this comparison, averaging 76.9 versus 48.8. Inside this category, MMMU-Pro is the benchmark that creates the most daylight between them.

Which is better for instruction following, GPT-OSS 120B or Qwen3.5-122B-A10B?

Qwen3.5-122B-A10B has the edge for instruction following in this comparison, averaging 93.4 versus 79. Inside this category, IFEval is the benchmark that creates the most daylight between them.

Which is better for multilingual tasks, GPT-OSS 120B or Qwen3.5-122B-A10B?

Qwen3.5-122B-A10B has the edge for multilingual tasks in this comparison, averaging 82.2 versus 70.7. Inside this category, MMLU-ProX is the benchmark that creates the most daylight between them.

Last updated: March 31, 2026

Weekly LLM Benchmark Digest

Get notified when new models drop, benchmark scores change, or the leaderboard shifts. One email per week.

Free. No spam. Unsubscribe anytime. We only store derived location metadata for consent routing.