Side-by-side benchmark comparison across agentic, coding, multimodal, knowledge, reasoning, and math workflows.
GPT-5.3 Codex
85
Winner · 4/8 categoriesQwen3.5-27B
71
3/8 categoriesGPT-5.3 Codex· Qwen3.5-27B
Pick GPT-5.3 Codex if you want the stronger benchmark profile. Qwen3.5-27B only becomes the better choice if coding is the priority or you want the cheaper token bill.
GPT-5.3 Codex is clearly ahead on the aggregate, 85 to 71. The gap is large enough that you do not need to squint at the spreadsheet to see the difference.
GPT-5.3 Codex's sharpest advantage is in reasoning, where it averages 92.5 against 60.6. The single biggest benchmark swing on the page is Terminal-Bench 2.0, 77.3% to 41.6%. Qwen3.5-27B does hit back in coding, so the answer changes if that is the part of the workload you care about most.
GPT-5.3 Codex is also the more expensive model on tokens at $2.50 input / $10.00 output per 1M tokens, versus $0.00 input / $0.00 output per 1M tokens for Qwen3.5-27B. That is roughly Infinityx on output cost alone. GPT-5.3 Codex gives you the larger context window at 400K, compared with 262K for Qwen3.5-27B.
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.
| Benchmark | GPT-5.3 Codex | Qwen3.5-27B |
|---|---|---|
| AgenticGPT-5.3 Codex wins | ||
| Terminal-Bench 2.0 | 77.3% | 41.6% |
| BrowseComp | 88% | 61% |
| OSWorld-Verified | 64.7% | 56.2% |
| tau2-bench | — | 79% |
| CodingQwen3.5-27B wins | ||
| SWE-bench Verified | 85% | 72.4% |
| LiveCodeBench | 85% | 80.7% |
| SWE-bench Pro | 56.8% | — |
| SWE-Rebench | 58.2% | — |
| React Native Evals | 80.9% | — |
| Multimodal & GroundedGPT-5.3 Codex wins | ||
| MMMU-Pro | 89% | 75% |
| OfficeQA Pro | 94% | — |
| ReasoningGPT-5.3 Codex wins | ||
| BBH | 98% | — |
| LongBench v2 | 92% | 60.6% |
| MRCRv2 | 93% | — |
| KnowledgeQwen3.5-27B wins | ||
| MMLU-Pro | 90% | 86.1% |
| HLE | 44% | — |
| FrontierScience | 90% | — |
| SimpleQA | 95% | — |
| SuperGPQA | — | 65.6% |
| GPQA | — | 85.5% |
| Instruction FollowingQwen3.5-27B wins | ||
| IFEval | 93% | 95% |
| MultilingualGPT-5.3 Codex wins | ||
| MGSM | 96% | — |
| MMLU-ProX | 91% | 82.2% |
| Mathematics | ||
| AIME 2023 | 99% | — |
| AIME 2024 | 99% | — |
| AIME 2025 | 98% | — |
| HMMT Feb 2023 | 95% | — |
| HMMT Feb 2024 | 97% | — |
| HMMT Feb 2025 | 96% | — |
| BRUMO 2025 | 96% | — |
| MATH-500 | 99% | — |
GPT-5.3 Codex is ahead overall, 85 to 71. The biggest single separator in this matchup is Terminal-Bench 2.0, where the scores are 77.3% and 41.6%.
Qwen3.5-27B has the edge for knowledge tasks in this comparison, averaging 80.6 versus 76.9. Inside this category, MMLU-Pro is the benchmark that creates the most daylight between them.
Qwen3.5-27B has the edge for coding in this comparison, averaging 77.6 versus 68.6. Inside this category, SWE-bench Verified is the benchmark that creates the most daylight between them.
GPT-5.3 Codex has the edge for reasoning in this comparison, averaging 92.5 versus 60.6. Inside this category, LongBench v2 is the benchmark that creates the most daylight between them.
GPT-5.3 Codex has the edge for agentic tasks in this comparison, averaging 75.6 versus 51.6. Inside this category, Terminal-Bench 2.0 is the benchmark that creates the most daylight between them.
GPT-5.3 Codex has the edge for multimodal and grounded tasks in this comparison, averaging 91.3 versus 75. Inside this category, MMMU-Pro is the benchmark that creates the most daylight between them.
Qwen3.5-27B has the edge for instruction following in this comparison, averaging 95 versus 93. Inside this category, IFEval is the benchmark that creates the most daylight between them.
GPT-5.3 Codex has the edge for multilingual tasks in this comparison, averaging 92.8 versus 82.2. Inside this category, MMLU-ProX is the benchmark that creates the most daylight between them.
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