Model comparison
GPT-5.1-Codex-Max vs Mistral Medium 3.5 128B
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 #95 (Estimated); Mistral Medium 3.5 128B unranked (Not scored). Intervals and evidence labels describe ranking uncertainty, not a guarantee for a specific workload.
Evidence parity. GPT-5.1-Codex-Max and Mistral Medium 3.5 128B share 12 comparable benchmark results. 0 of 8 categories are comparable. 1 result is unique to GPT-5.1-Codex-Max; 13 to Mistral Medium 3.5 128B.
Updated July 27, 2026- Shared results
- 12
- GPT-5.1-Codex-Max only
- 1
- Mistral Medium 3.5 128B only
- 13
- Comparable categories
- 0 / 8
Benchmark data for GPT-5.1-Codex-Max and Mistral Medium 3.5 128B 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 $1.50 input / $7.50 output per 1M tokens for Mistral Medium 3.5 128B. GPT-5.1-Codex-Max has the larger context window at 400K, compared with 256K for Mistral Medium 3.5 128B.
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 | Mistral Medium 3.5 128B |
|---|---|---|---|
| Coding | GPT-5.1-Codex-MaxNot measured | MarginNo overlap | Mistral Medium 3.5 128B77.6 |
Operational comparison
Runtime and commercial metrics are compared only when both models have a complete sourced value.
| Metric | GPT-5.1-Codex-Max | Mistral Medium 3.5 128B | Comparison |
|---|---|---|---|
| Input / output priceUSD per 1M tokens | GPT-5.1-Codex-Max$1.25 input / $10 output | Mistral Medium 3.5 128B$1.5 input / $7.5 output | Mistral Medium 3.5 128B has the lower combined listed price. |
| Generation speedtokens per second | GPT-5.1-Codex-MaxNot available | Mistral Medium 3.5 128BNot available | A complete speed comparison is not available. |
| First-answer latencyseconds to first token | GPT-5.1-Codex-MaxNot available | Mistral Medium 3.5 128BNot available | A complete latency comparison is not available. |
| Context windowmaximum listed tokens | GPT-5.1-Codex-Max400K | Mistral Medium 3.5 128B256K | GPT-5.1-Codex-Max lists the larger context window. |
Benchmark Deep Dive
Agentic11 benchmarks
| Benchmark | GPT-5.1-Codex-Max | Mistral Medium 3.5 128B | Result |
|---|---|---|---|
| τ²-bench resultsSource | 83% | 94.2% | Mistral Medium 3.5 128B leads |
| τ³-bench resultsSource | — | 91.4% | Not comparable |
| AA Agentic IndexSource | — | 19.0% | Not comparable |
| GDPval-AASource | — | 21.6% | Not comparable |
| GDPval-AASource | — | 933 | Not comparable |
| Gert LabsSource | — | 39.10% | Not comparable |
| AA EnterpriseOps-GymSource | — | 33.7% | Not comparable |
| AA Harvey LABSource | — | 69.1% | Not comparable |
| terminalBenchHardSource | — | 33.3% | Not comparable |
| AA BriefcaseSource | — | 516 | Not comparable |
| AA Tau3 BankingSource | — | 14.4% | Not comparable |
Coding4 benchmarks
Reasoning2 benchmarks
Knowledge7 benchmarks
| Benchmark | GPT-5.1-Codex-Max | Mistral Medium 3.5 128B | Result |
|---|---|---|---|
| Artificial Analysis Intelligence IndexSource | 34.7% | 29.9% | GPT-5.1-Codex-Max leads |
| AA-GPQA DiamondSource | 86.0% | 74.8% | GPT-5.1-Codex-Max leads |
| AA-HLESource | 23.4% | 12.8% | GPT-5.1-Codex-Max leads |
| AA-Omniscience IndexSource | -6.0% | -36.3% | GPT-5.1-Codex-Max leads |
| AA-Omniscience AccuracySource | 39.2% | 25.1% | GPT-5.1-Codex-Max leads |
| AA-Omniscience Hallucination RateSource | 74.4% | 82.0% | GPT-5.1-Codex-Max leads |
| AA Openness IndexSource | — | 33.3% | Not comparable |
Multimodal1 benchmarks
| Benchmark | GPT-5.1-Codex-Max | Mistral Medium 3.5 128B | Result |
|---|---|---|---|
| AA-MMMU-ProSource | 72.5% | 64.9% | GPT-5.1-Codex-Max leads |
Inst. Following1 benchmarks
| Benchmark | GPT-5.1-Codex-Max | Mistral Medium 3.5 128B | Result |
|---|---|---|---|
| AA-IFBenchSource | 70.0% | 68.8% | GPT-5.1-Codex-Max leads |
Frequently Asked Questions (3)
Can I compare GPT-5.1-Codex-Max and Mistral Medium 3.5 128B 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 Mistral Medium 3.5 128B today?
GPT-5.1-Codex-Max: $1.25 input / $10.00 output per 1M tokens Mistral Medium 3.5 128B: $1.50 input / $7.50 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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