Model comparison
GPT-5.4 nano vs Mistral Medium 3.5 128B
Head-to-head evidence from 16 shared benchmark results across 6 categories. Overall scores shown here use the public BenchAlign v5 ranking lane.
Public leaderboard positions: GPT-5.4 nano #28 (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 nano and Mistral Medium 3.5 128B share 16 comparable benchmark results. 0 of 8 categories are comparable. 13 results are unique to GPT-5.4 nano; 9 to Mistral Medium 3.5 128B.
Updated July 27, 2026- Shared results
- 16
- GPT-5.4 nano only
- 13
- Mistral Medium 3.5 128B only
- 9
- Comparable categories
- 0 / 8
Benchmark data for GPT-5.4 nano and Mistral Medium 3.5 128B is coming soon on BenchLM.
Confidence note. This is a partial-evidence comparison with 16 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.
Mistral Medium 3.5 128B is priced at $1.50 input / $7.50 output per 1M tokens, versus $0.20 input / $1.25 output per 1M tokens for GPT-5.4 nano. GPT-5.4 nano 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-5.4 nano | Δ | Mistral Medium 3.5 128B |
|---|---|---|---|
| Agentic | GPT-5.4 nano42.9 | MarginNo overlap | Mistral Medium 3.5 128BNot measured |
| Coding | GPT-5.4 nanoNot measured | MarginNo overlap | Mistral Medium 3.5 128B77.6 |
| Knowledge | GPT-5.4 nano43.8 | MarginNo overlap | Mistral Medium 3.5 128BNot measured |
| Math | GPT-5.4 nano21.0 | MarginNo overlap | Mistral Medium 3.5 128BNot measured |
| Multimodal | GPT-5.4 nano66.1 | 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 nano | Mistral Medium 3.5 128B | Comparison |
|---|---|---|---|
| Input / output priceUSD per 1M tokens | GPT-5.4 nano$0.2 input / $1.25 output | Mistral Medium 3.5 128B$1.5 input / $7.5 output | GPT-5.4 nano has the lower combined listed price. |
| Generation speedtokens per second | GPT-5.4 nano191 tok/s | Mistral Medium 3.5 128BNot available | A complete speed comparison is not available. |
| First-answer latencyseconds to first token | GPT-5.4 nano3.64 s | Mistral Medium 3.5 128BNot available | A complete latency comparison is not available. |
| Context windowmaximum listed tokens | GPT-5.4 nano400K | Mistral Medium 3.5 128B256K | GPT-5.4 nano lists the larger context window. |
Benchmark Deep Dive
Agentic16 benchmarks
| Benchmark | GPT-5.4 nano | Mistral Medium 3.5 128B | Result |
|---|---|---|---|
| Terminal-Bench 2.0Source | 46.3% | — | Not comparable |
| OSWorld-VerifiedSource | 39% | — | Not comparable |
| MCP AtlasSource | 56.1% | — | Not comparable |
| ToolathlonSource | 35.5% | — | Not comparable |
| τ²-bench resultsSource | 76% | 94.2% | Mistral Medium 3.5 128B leads |
| AA Agentic IndexSource | 27.5% | 19.0% | GPT-5.4 nano leads |
| APEX-Agents-AASource | 24.9% | — | Not comparable |
| GDPval-AASource | 30.1% | 21.6% | GPT-5.4 nano leads |
| GDPval-AASource | 1101 | 933 | GPT-5.4 nano leads |
| τ³-bench resultsSource | — | 91.4% | 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
Knowledge10 benchmarks
| Benchmark | GPT-5.4 nano | Mistral Medium 3.5 128B | Result |
|---|---|---|---|
| GPQASource | 82.8% | — | Not comparable |
| HLESource | 37.7% | — | Not comparable |
| HLE w/o toolsSource | 24.3% | — | Not comparable |
| Artificial Analysis Intelligence IndexSource | 38.2% | 29.9% | GPT-5.4 nano leads |
| AA-GPQA DiamondSource | 81.7% | 74.8% | GPT-5.4 nano leads |
| AA-HLESource | 26.5% | 12.8% | GPT-5.4 nano leads |
| AA-Omniscience IndexSource | -29.5% | -36.3% | GPT-5.4 nano leads |
| AA-Omniscience AccuracySource | 25.4% | 25.1% | GPT-5.4 nano leads |
| AA-Omniscience Hallucination RateSource | 73.6% | 82.0% | GPT-5.4 nano leads |
| AA Openness IndexSource | — | 33.3% | Not comparable |
Math2 benchmarks
Multimodal3 benchmarks
Inst. Following1 benchmarks
| Benchmark | GPT-5.4 nano | Mistral Medium 3.5 128B | Result |
|---|---|---|---|
| AA-IFBenchSource | 75.9% | 68.8% | GPT-5.4 nano leads |
Frequently Asked Questions (3)
Can I compare GPT-5.4 nano 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-5.4 nano and Mistral Medium 3.5 128B today?
GPT-5.4 nano: $0.20 input / $1.25 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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