Model comparison
GPT-5.1-Codex vs Qwen3.5-122B-A10B
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 #99 (Estimated); Qwen3.5-122B-A10B #47 (Supported). Intervals and evidence labels describe ranking uncertainty, not a guarantee for a specific workload.
Evidence parity. GPT-5.1-Codex and Qwen3.5-122B-A10B share 12 comparable benchmark results. 0 of 8 categories are comparable. 4 results are unique to GPT-5.1-Codex; 19 to Qwen3.5-122B-A10B.
Updated July 23, 2026- Shared results
- 12
- GPT-5.1-Codex only
- 4
- Qwen3.5-122B-A10B only
- 19
- Comparable categories
- 0 / 8
Benchmark data for GPT-5.1-Codex and Qwen3.5-122B-A10B 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 has the larger context window at 400K, compared with 262K for Qwen3.5-122B-A10B.
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 | Δ | Qwen3.5-122B-A10B |
|---|---|---|---|
| Agentic | GPT-5.1-CodexNot measured | MarginNo overlap | Qwen3.5-122B-A10B56.4 |
| Coding | GPT-5.1-CodexNot measured | MarginNo overlap | Qwen3.5-122B-A10B72.0 |
| Reasoning | GPT-5.1-CodexNot measured | MarginNo overlap | Qwen3.5-122B-A10B60.2 |
| Knowledge | GPT-5.1-CodexNot measured | MarginNo overlap | Qwen3.5-122B-A10B83.6 |
| Multilingual | GPT-5.1-CodexNot measured | MarginNo overlap | Qwen3.5-122B-A10B82.2 |
| Multimodal | GPT-5.1-CodexNot measured | MarginNo overlap | Qwen3.5-122B-A10B77.2 |
| Inst. Following | GPT-5.1-CodexNot measured | MarginNo overlap | Qwen3.5-122B-A10B93.4 |
Operational comparison
Runtime and commercial metrics are compared only when both models have a complete sourced value.
| Metric | GPT-5.1-Codex | Qwen3.5-122B-A10B | Comparison |
|---|---|---|---|
| Input / output priceUSD per 1M tokens | GPT-5.1-CodexNot available | Qwen3.5-122B-A10B$0 input / $0 output | A complete price comparison is not available. |
| Generation speedtokens per second | GPT-5.1-CodexNot available | Qwen3.5-122B-A10BNot available | A complete speed comparison is not available. |
| First-answer latencyseconds to first token | GPT-5.1-CodexNot available | Qwen3.5-122B-A10BNot available | A complete latency comparison is not available. |
| Context windowmaximum listed tokens | GPT-5.1-Codex400K | Qwen3.5-122B-A10B262K | GPT-5.1-Codex lists the larger context window. |
Benchmark Deep Dive
Agentic9 benchmarks
| Benchmark | GPT-5.1-Codex | Qwen3.5-122B-A10B | Result |
|---|---|---|---|
| τ²-bench resultsSource | 83% | 93.6% | Qwen3.5-122B-A10B leads |
| Gert LabsSource | 49.68% | — | Not comparable |
| JobBenchSource | 26.2% | — | Not comparable |
| Terminal-Bench 2.0Source | — | 49.4% | Not comparable |
| BrowseCompSource | — | 63.8% | Not comparable |
| OSWorld-VerifiedSource | — | 58% | Not comparable |
| AA Agentic IndexSource | — | 20.7% | Not comparable |
| GDPval-AASource | — | 23.9% | Not comparable |
| GDPval-AASource | — | 978 | Not comparable |
Coding4 benchmarks
Reasoning3 benchmarks
Knowledge9 benchmarks
| Benchmark | GPT-5.1-Codex | Qwen3.5-122B-A10B | Result |
|---|---|---|---|
| Artificial Analysis Intelligence IndexSource | 34.7% | 32.3% | GPT-5.1-Codex leads |
| AA-GPQA DiamondSource | 86.0% | 85.7% | GPT-5.1-Codex leads |
| AA-HLESource | 23.4% | 23.4% | Tie |
| AA-Omniscience IndexSource | -6.0% | -39.6% | GPT-5.1-Codex leads |
| AA-Omniscience AccuracySource | 39.2% | 24.7% | GPT-5.1-Codex leads |
| AA-Omniscience Hallucination RateSource | 74.4% | 85.5% | GPT-5.1-Codex leads |
| MMLU-ProSource | — | 86.7% | Not comparable |
| SuperGPQASource | — | 67.1% | Not comparable |
| GPQASource | — | 86.6% | Not comparable |
Multilingual1 benchmarks
| Benchmark | GPT-5.1-Codex | Qwen3.5-122B-A10B | Result |
|---|---|---|---|
| MMLU-ProXSource | — | 82.2% | Not comparable |
Multimodal7 benchmarks
| Benchmark | GPT-5.1-Codex | Qwen3.5-122B-A10B | Result |
|---|---|---|---|
| AA-MMMU-ProSource | 72.5% | 75.0% | Qwen3.5-122B-A10B leads |
| Design Arena WebsiteSource | 1191 | — | Not comparable |
| MMMUSource | — | 83.9% | Not comparable |
| MMVUSource | — | 74.7% | Not comparable |
| MathVisionSource | — | 86.2% | Not comparable |
| CharXivSource | — | 77.2% | Not comparable |
| V*Source | — | 93.2% | Not comparable |
Frequently Asked Questions (3)
Can I compare GPT-5.1-Codex and Qwen3.5-122B-A10B 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 and Qwen3.5-122B-A10B today?
Qwen3.5-122B-A10B: $0.00 input / $0.00 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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