Model comparison
GPT-5.4 vs Mistral Medium 3.5 128B
Head-to-head evidence from 17 shared benchmark results across 6 categories. Overall scores shown here use the public BenchAlign v5 ranking lane.
Public leaderboard positions: GPT-5.4 #10 (Supported); 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-5.4 and Mistral Medium 3.5 128B share 17 comparable benchmark results. 1 of 8 categories are comparable. 37 results are unique to GPT-5.4; 8 to Mistral Medium 3.5 128B.
Updated July 27, 2026- Shared results
- 17
- GPT-5.4 only
- 37
- Mistral Medium 3.5 128B only
- 8
- Comparable categories
- 1 / 8
Treat this as a split decision. GPT-5.4 makes more sense if you need the larger 1.05M context window; Mistral Medium 3.5 128B is the better fit if coding is the priority or you want the cheaper token bill.
Confidence note. This is a partial-evidence comparison with 17 shared benchmark results across 6 evidence categories; 1 of 8 categories currently have scoreable aggregates for both models. Treat the verdict as directional until coverage is more balanced.
Why this result
GPT-5.4 and Mistral Medium 3.5 128B finish on the same BenchAlign overall score, so this is less about a single winner and more about where the edge shows up. The BenchAlign headline says tie; the benchmark table is where the real choice happens.
GPT-5.4 is also the more expensive model on tokens at $2.50 input / $15.00 output per 1M tokens, versus $1.50 input / $7.50 output per 1M tokens for Mistral Medium 3.5 128B. That is roughly 2.0x on output cost alone. GPT-5.4 gives you the larger context window at 1.05M, 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-5.4 | Δ | Mistral Medium 3.5 128B |
|---|---|---|---|
| Coding | GPT-5.457.7 | Margin→ 19.9 | Mistral Medium 3.5 128B77.6 |
| Agentic | GPT-5.477.2 | MarginNo overlap | Mistral Medium 3.5 128BNot measured |
| Reasoning | GPT-5.474.0 | MarginNo overlap | Mistral Medium 3.5 128BNot measured |
| Knowledge | GPT-5.457.6 | MarginNo overlap | Mistral Medium 3.5 128BNot measured |
| Math | GPT-5.442.5 | MarginNo overlap | Mistral Medium 3.5 128BNot measured |
| Multimodal | GPT-5.473.2 | MarginNo overlap | Mistral Medium 3.5 128BNot measured |
Operational comparison
Runtime and commercial metrics are compared only when both models have a complete sourced value.
| Metric | GPT-5.4 | Mistral Medium 3.5 128B | Comparison |
|---|---|---|---|
| Input / output priceUSD per 1M tokens | GPT-5.4$2.5 input / $15 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-5.474 tok/s | Mistral Medium 3.5 128BNot available | A complete speed comparison is not available. |
| First-answer latencyseconds to first token | GPT-5.4151.79 s | Mistral Medium 3.5 128BNot available | A complete latency comparison is not available. |
| Context windowmaximum listed tokens | GPT-5.41.05M | Mistral Medium 3.5 128B256K | GPT-5.4 lists the larger context window. |
Benchmark Deep Dive
Agentic23 benchmarks
| Benchmark | GPT-5.4 | Mistral Medium 3.5 128B | Result |
|---|---|---|---|
| Terminal-Bench 2.0Source | 75.1% | — | Not comparable |
| CyberGymSource | 79.0% | — | Not comparable |
| BrowseCompSource | 82.7% | — | Not comparable |
| OSWorld-VerifiedSource | 75% | — | Not comparable |
| MCP AtlasSource | 70.6% | — | Not comparable |
| ToolathlonSource | 54.6% | — | Not comparable |
| τ²-bench resultsSource | 87.1% | 94.2% | Mistral Medium 3.5 128B leads |
| Claw-EvalSource | 60.3% | — | Not comparable |
| DeepSearchQASource | 73.6% | — | Not comparable |
| AA Agentic IndexSource | 41.1% | 19.0% | GPT-5.4 leads |
| APEX-Agents-AASource | 33.3% | — | Not comparable |
| GDPval-AASource | 44.6% | 21.6% | GPT-5.4 leads |
| GDPval-AASource | 1392 | 933 | GPT-5.4 leads |
| Gert LabsSource | 64.89% | 39.10% | GPT-5.4 leads |
| ResearchClawBenchSource | 15.3% | — | Not comparable |
| JobBenchSource | 38.9% | — | Not comparable |
| ExploitGymSource | 6.0% | — | Not comparable |
| τ³-bench resultsSource | — | 91.4% | 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 |
CodingMistral Medium 3.5 128B wins7 benchmarks
| Benchmark | GPT-5.4 | Mistral Medium 3.5 128B | Result |
|---|---|---|---|
| LiveCodeBench ProSource | 87.5% | — | Not comparable |
| SWE-bench ProSource | 57.7% | — | Not comparable |
| React Native EvalsSource | 85.3% | — | Not comparable |
| Vibe Code BenchSource | 67.42% | — | Not comparable |
| AA Coding IndexSource | 71.0% | 46.9% | GPT-5.4 leads |
| AA-SciCodeSource | 56.6% | 39.6% | GPT-5.4 leads |
| SWE-bench VerifiedSource | — | 77.6% | Not comparable |
Reasoning4 benchmarks
Knowledge14 benchmarks
| Benchmark | GPT-5.4 | Mistral Medium 3.5 128B | Result |
|---|---|---|---|
| GPQASource | 92.8% | — | Not comparable |
| HLESource | 52.1% | — | Not comparable |
| HLE w/o toolsSource | 39.8% | — | Not comparable |
| GPQA-DSource | 92.8% | — | Not comparable |
| HealthBench HardSource | 40.1% | — | Not comparable |
| MedXpertQA (Text)Source | 59.6% | — | Not comparable |
| Artificial Analysis Intelligence IndexSource | 51.4% | 29.9% | GPT-5.4 leads |
| AA-GPQA DiamondSource | 92.0% | 74.8% | GPT-5.4 leads |
| AA-HLESource | 41.6% | 12.8% | GPT-5.4 leads |
| AA-Omniscience IndexSource | 5.7% | -36.3% | GPT-5.4 leads |
| AA-Omniscience AccuracySource | 50.0% | 25.1% | GPT-5.4 leads |
| AA-Omniscience Hallucination RateSource | 88.6% | 82.0% | Mistral Medium 3.5 128B leads |
| HealthBench ProfessionalSource | 48.1% | — | Not comparable |
| AA Openness IndexSource | — | 33.3% | Not comparable |
Math2 benchmarks
Multimodal11 benchmarks
| Benchmark | GPT-5.4 | Mistral Medium 3.5 128B | Result |
|---|---|---|---|
| MMMU-ProSource | 81.2% | — | Not comparable |
| OfficeQA ProSource | 53.2% | — | Not comparable |
| MMMU-Pro w/ PythonSource | 82.1% | — | Not comparable |
| CharXivSource | 82.8% | — | Not comparable |
| ERQASource | 65.4% | — | Not comparable |
| SimpleVQASource | 61.1% | — | Not comparable |
| ScreenSpot ProSource | 85.4% | — | Not comparable |
| ZeroBenchSource | 41.0% | — | Not comparable |
| MedXpertQA (MM)Source | 77.1% | — | Not comparable |
| AA-MMMU-ProSource | 78.4% | 64.9% | GPT-5.4 leads |
| Design Arena WebsiteSource | 1245 | — | Not comparable |
Inst. Following1 benchmarks
| Benchmark | GPT-5.4 | Mistral Medium 3.5 128B | Result |
|---|---|---|---|
| AA-IFBenchSource | 73.9% | 68.8% | GPT-5.4 leads |
Frequently Asked Questions (2)
Which is better, GPT-5.4 or Mistral Medium 3.5 128B?
GPT-5.4 and Mistral Medium 3.5 128B are tied on the BenchAlign overall score, so the right pick depends on which category matters most for your use case.
Which is better for coding, GPT-5.4 or Mistral Medium 3.5 128B?
Mistral Medium 3.5 128B has the edge for coding in this comparison, averaging 77.6 versus 57.7. Inside this category, AA Coding Index is the benchmark that creates the most daylight between them.
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