Model comparison
GPT-OSS 120B vs Mistral Medium 3.5 128B
Head-to-head evidence from 20 shared benchmark results across 5 categories. Overall scores shown here use the public BenchAlign v5 ranking lane.
Public leaderboard positions: GPT-OSS 120B #122 (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-OSS 120B and Mistral Medium 3.5 128B share 20 comparable benchmark results. 0 of 8 categories are comparable. 8 results are unique to GPT-OSS 120B; 5 to Mistral Medium 3.5 128B.
Updated July 27, 2026- Shared results
- 20
- GPT-OSS 120B only
- 8
- Mistral Medium 3.5 128B only
- 5
- Comparable categories
- 0 / 8
Benchmark data for GPT-OSS 120B and Mistral Medium 3.5 128B is coming soon on BenchLM.
Confidence note. This is a partial-evidence comparison with 20 shared benchmark results across 5 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 $0.00 input / $0.00 output per 1M tokens for GPT-OSS 120B. Mistral Medium 3.5 128B has the larger context window at 256K, compared with 128K for GPT-OSS 120B.
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-OSS 120B | Δ | Mistral Medium 3.5 128B |
|---|---|---|---|
| Coding | GPT-OSS 120BNot 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-OSS 120B | Mistral Medium 3.5 128B | Comparison |
|---|---|---|---|
| Input / output priceUSD per 1M tokens | GPT-OSS 120B$0 input / $0 output | Mistral Medium 3.5 128B$1.5 input / $7.5 output | GPT-OSS 120B has the lower combined listed price. |
| Generation speedtokens per second | GPT-OSS 120B262 tok/s | Mistral Medium 3.5 128BNot available | A complete speed comparison is not available. |
| First-answer latencyseconds to first token | GPT-OSS 120B0.79 s | Mistral Medium 3.5 128BNot available | A complete latency comparison is not available. |
| Context windowmaximum listed tokens | GPT-OSS 120B128K | Mistral Medium 3.5 128B256K | Mistral Medium 3.5 128B lists the larger context window. |
Benchmark Deep Dive
Agentic13 benchmarks
| Benchmark | GPT-OSS 120B | Mistral Medium 3.5 128B | Result |
|---|---|---|---|
| AA Agentic IndexSource | 13.2% | 19.0% | Mistral Medium 3.5 128B leads |
| APEX-Agents-AASource | 3.1% | — | Not comparable |
| τ²-bench resultsSource | 65.8% | 94.2% | Mistral Medium 3.5 128B leads |
| GDPval-AASource | 15.1% | 21.6% | Mistral Medium 3.5 128B leads |
| GDPval-AASource | 802 | 933 | Mistral Medium 3.5 128B leads |
| Gert LabsSource | 29.61% | 39.10% | Mistral Medium 3.5 128B leads |
| AA ITBenchSource | 5.6% | — | Not comparable |
| AA EnterpriseOps-GymSource | 25.5% | 33.7% | Mistral Medium 3.5 128B leads |
| AA Harvey LABSource | 13.9% | 69.1% | Mistral Medium 3.5 128B leads |
| terminalBenchHardSource | 23.5% | 33.3% | Mistral Medium 3.5 128B leads |
| τ³-bench resultsSource | — | 91.4% | Not comparable |
| AA BriefcaseSource | — | 516 | Not comparable |
| AA Tau3 BankingSource | — | 14.4% | Not comparable |
Coding5 benchmarks
| Benchmark | GPT-OSS 120B | Mistral Medium 3.5 128B | Result |
|---|---|---|---|
| React Native EvalsSource | 71.6% | — | Not comparable |
| AA Coding IndexSource | 30.4% | 46.9% | Mistral Medium 3.5 128B leads |
| AA-SciCodeSource | 38.9% | 39.6% | Mistral Medium 3.5 128B leads |
| AA LiveCodeBenchSource | 87.8% | — | Not comparable |
| SWE-bench VerifiedSource | — | 77.6% | Not comparable |
Reasoning2 benchmarks
Knowledge8 benchmarks
| Benchmark | GPT-OSS 120B | Mistral Medium 3.5 128B | Result |
|---|---|---|---|
| Artificial Analysis Intelligence IndexSource | 23.8% | 29.9% | Mistral Medium 3.5 128B leads |
| AA-GPQA DiamondSource | 78.2% | 74.8% | GPT-OSS 120B leads |
| AA-HLESource | 18.5% | 12.8% | GPT-OSS 120B leads |
| AA-Omniscience IndexSource | -50.0% | -36.3% | Mistral Medium 3.5 128B leads |
| AA-Omniscience AccuracySource | 21.5% | 25.1% | Mistral Medium 3.5 128B leads |
| AA-Omniscience Hallucination RateSource | 91.2% | 82.0% | Mistral Medium 3.5 128B leads |
| AA Openness IndexSource | 38.9% | 33.3% | GPT-OSS 120B leads |
| AA MMLU-ProSource | 80.8% | — | Not comparable |
Math1 benchmarks
| Benchmark | GPT-OSS 120B | Mistral Medium 3.5 128B | Result |
|---|---|---|---|
| AA AIME 2025Source | 93.4% | — | Not comparable |
Multilingual1 benchmarks
| Benchmark | GPT-OSS 120B | Mistral Medium 3.5 128B | Result |
|---|---|---|---|
| AA Global-MMLU-LiteSource | 82.8% | — | Not comparable |
Multimodal2 benchmarks
Inst. Following1 benchmarks
| Benchmark | GPT-OSS 120B | Mistral Medium 3.5 128B | Result |
|---|---|---|---|
| AA-IFBenchSource | 69.0% | 68.8% | GPT-OSS 120B leads |
Frequently Asked Questions (3)
Can I compare GPT-OSS 120B 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-OSS 120B and Mistral Medium 3.5 128B today?
GPT-OSS 120B: $0.00 input / $0.00 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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