Model comparison
GPT-5.1-Codex-Max vs Qwen3.5 397B
Head-to-head evidence from 12 shared benchmark results across 6 categories. Overall scores shown here use the public BenchAlign v5 ranking lane.
Public leaderboard positions: GPT-5.1-Codex-Max #90 (Estimated); Qwen3.5 397B #71 (Estimated). Intervals and evidence labels describe ranking uncertainty, not a guarantee for a specific workload.
Evidence parity. GPT-5.1-Codex-Max and Qwen3.5 397B share 12 comparable benchmark results. 0 of 8 categories are comparable. 1 result is unique to GPT-5.1-Codex-Max; 43 to Qwen3.5 397B.
Updated July 20, 2026- Shared results
- 12
- GPT-5.1-Codex-Max only
- 1
- Qwen3.5 397B only
- 43
- Comparable categories
- 0 / 8
Benchmark data for GPT-5.1-Codex-Max and Qwen3.5 397B is coming soon on BenchLM.
Confidence note. This is a partial-evidence comparison with 12 shared benchmark results across 6 evidence categories; 0 of 8 categories currently have scoreable aggregates for both models. Treat the verdict as directional until coverage is more balanced.
Why this result
BenchLM has partial data for these models, but not enough overlapping benchmark coverage to produce a fair score-level comparison yet.
GPT-5.1-Codex-Max is priced at $1.25 input / $10.00 output per 1M tokens, versus $0.60 input / $3.60 output per 1M tokens for Qwen3.5 397B. GPT-5.1-Codex-Max has the larger context window at 400K, compared with 128K for Qwen3.5 397B.
Category breakdown
Exact category averages are shown below. Not measured means BenchLM does not have enough sourced public coverage for that model and category.
| Category | GPT-5.1-Codex-Max | Δ | Qwen3.5 397B |
|---|---|---|---|
| Agentic | GPT-5.1-Codex-MaxNot measured | MarginNo overlap | Qwen3.5 397B56.5 |
| Coding | GPT-5.1-Codex-MaxNot measured | MarginNo overlap | Qwen3.5 397B66.5 |
| Reasoning | GPT-5.1-Codex-MaxNot measured | MarginNo overlap | Qwen3.5 397B63.2 |
| Knowledge | GPT-5.1-Codex-MaxNot measured | MarginNo overlap | Qwen3.5 397B56.6 |
| Math | GPT-5.1-Codex-MaxNot measured | MarginNo overlap | Qwen3.5 397B90.6 |
| Multilingual | GPT-5.1-Codex-MaxNot measured | MarginNo overlap | Qwen3.5 397B84.7 |
| Multimodal | GPT-5.1-Codex-MaxNot measured | MarginNo overlap | Qwen3.5 397B79.6 |
| Inst. Following | GPT-5.1-Codex-MaxNot measured | MarginNo overlap | Qwen3.5 397B92.6 |
Operational comparison
Runtime and commercial metrics are compared only when both models have a complete sourced value.
| Metric | GPT-5.1-Codex-Max | Qwen3.5 397B | Comparison |
|---|---|---|---|
| Input / output priceUSD per 1M tokens | GPT-5.1-Codex-Max$1.25 input / $10 output | Qwen3.5 397B$0.6 input / $3.6 output | Qwen3.5 397B has the lower combined listed price. |
| Generation speedtokens per second | GPT-5.1-Codex-MaxNot available | Qwen3.5 397B96 tok/s | A complete speed comparison is not available. |
| First-answer latencyseconds to first token | GPT-5.1-Codex-MaxNot available | Qwen3.5 397B2.44 s | A complete latency comparison is not available. |
| Context windowmaximum listed tokens | GPT-5.1-Codex-Max400K | Qwen3.5 397B128K | GPT-5.1-Codex-Max lists the larger context window. |
Benchmark Deep Dive
Agentic18 benchmarks
| Benchmark | GPT-5.1-Codex-Max | Qwen3.5 397B | Result |
|---|---|---|---|
| τ²-bench resultsSource | 83% | 95.6% | Qwen3.5 397B leads |
| Terminal-Bench 2.0Source | — | 52.5% | Not comparable |
| BrowseCompSource | — | 62% | Not comparable |
| Claw-EvalSource | — | 56.8% | Not comparable |
| QwenClawBenchSource | — | 51.8% | Not comparable |
| τ³-bench resultsSource | — | 68.4% | Not comparable |
| VITA-BenchSource | — | 43.7% | Not comparable |
| DeepPlanningSource | — | 37.6% | Not comparable |
| ToolathlonSource | — | 36.3% | Not comparable |
| MCP AtlasSource | — | 46.1% | Not comparable |
| MCP-TasksSource | — | 74.2% | Not comparable |
| WideResearchSource | — | 74.0% | Not comparable |
| Gert LabsSource | — | 46.76% | Not comparable |
| ResearchClawBenchSource | — | 14.2% | Not comparable |
| AA Agentic IndexSource | — | 19.9% | Not comparable |
| APEX-Agents-AASource | — | 15.3% | Not comparable |
| GDPval-AASource | — | 23.1% | Not comparable |
| GDPval-AASource | — | 962 | Not comparable |
Coding6 benchmarks
| Benchmark | GPT-5.1-Codex-Max | Qwen3.5 397B | Result |
|---|---|---|---|
| Vibe Code BenchSource | 22.17% | — | Not comparable |
| AA-SciCodeSource | 40.2% | 42.0% | Qwen3.5 397B leads |
| SWE-bench VerifiedSource | — | 76.2% | Not comparable |
| LiveCodeBench v6Source | — | 83.6% | Not comparable |
| SWE-bench ProSource | — | 50.9% | Not comparable |
| AA Coding IndexSource | — | 48.2% | Not comparable |
Reasoning4 benchmarks
Knowledge12 benchmarks
| Benchmark | GPT-5.1-Codex-Max | Qwen3.5 397B | Result |
|---|---|---|---|
| Artificial Analysis Intelligence IndexSource | 34.7% | 33.7% | GPT-5.1-Codex-Max leads |
| AA-GPQA DiamondSource | 86.0% | 89.3% | Qwen3.5 397B leads |
| AA-HLESource | 23.4% | 27.3% | Qwen3.5 397B leads |
| AA-Omniscience IndexSource | -6.0% | -29.8% | GPT-5.1-Codex-Max leads |
| AA-Omniscience AccuracySource | 39.2% | 31.4% | GPT-5.1-Codex-Max leads |
| AA-Omniscience Hallucination RateSource | 74.4% | 89.1% | GPT-5.1-Codex-Max leads |
| GPQASource | — | 88.4% | Not comparable |
| SuperGPQASource | — | 70.4% | Not comparable |
| MMLU-ProSource | — | 87.8% | Not comparable |
| MMLU-ReduxSource | — | 94.9% | Not comparable |
| C-EvalSource | — | 93% | Not comparable |
| HLESource | — | 28.7% | Not comparable |
Math5 benchmarks
Multilingual2 benchmarks
Multimodal7 benchmarks
| Benchmark | GPT-5.1-Codex-Max | Qwen3.5 397B | Result |
|---|---|---|---|
| AA-MMMU-ProSource | 72.5% | 77.3% | Qwen3.5 397B leads |
| MMMU-ProSource | — | 79% | Not comparable |
| MathVisionSource | — | 88.6% | Not comparable |
| CharXivSource | — | 80.8% | Not comparable |
| VideoMMMUSource | — | 84.7% | Not comparable |
| ScreenSpot ProSource | — | 65.6% | Not comparable |
| V*Source | — | 95.8% | Not comparable |
Frequently Asked Questions (3)
Can I compare GPT-5.1-Codex-Max and Qwen3.5 397B on BenchLM yet?
Not fully yet. BenchLM is tracking both models, but the sourced benchmark breakdown for this comparison is still coming soon.
Why does this comparison show “coming soon”?
BenchLM only shows category winners and benchmark-level calls when we have sourced results that can be compared fairly. For these models, the public benchmark coverage is not complete enough yet.
What data is available for GPT-5.1-Codex-Max and Qwen3.5 397B today?
GPT-5.1-Codex-Max: $1.25 input / $10.00 output per 1M tokens Qwen3.5 397B: $0.60 input / $3.60 output per 1M tokens Both model pages still include creator, context window, reasoning mode, and other metadata while benchmark coverage fills in.
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