Model comparison
GPT-5 nano vs Mistral Large 3
Head-to-head evidence from 0 shared benchmark results across 0 categories. Overall scores shown here use the public BenchAlign v5 ranking lane.
Public leaderboard positions: GPT-5 nano #146 (Estimated); Mistral Large 3 #118 (Supported). Intervals and evidence labels describe ranking uncertainty, not a guarantee for a specific workload.
Evidence parity. GPT-5 nano and Mistral Large 3 share 0 comparable benchmark results. 0 of 8 categories are comparable. 0 results are unique to GPT-5 nano; 16 to Mistral Large 3.
Updated July 24, 2026- Shared results
- 0
- GPT-5 nano only
- 0
- Mistral Large 3 only
- 16
- Comparable categories
- 0 / 8
Benchmark data for GPT-5 nano and Mistral Large 3 is coming soon on BenchLM.
Confidence note. This is a partial-evidence comparison with 0 shared benchmark results across 0 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 does not have sourced benchmark coverage for GPT-5 nano yet. This comparison is currently limited to metadata such as context window, reasoning mode, and pricing where available.
Mistral Large 3 is priced at $0.50 input / $1.50 output per 1M tokens, versus $0.05 input / $0.40 output per 1M tokens for GPT-5 nano. GPT-5 nano has the larger context window at 400K, compared with 128K for Mistral Large 3.
Operational comparison
Runtime and commercial metrics are compared only when both models have a complete sourced value.
| Metric | GPT-5 nano | Mistral Large 3 | Comparison |
|---|---|---|---|
| Input / output priceUSD per 1M tokens | GPT-5 nano$0.05 input / $0.4 output | Mistral Large 3$0.5 input / $1.5 output | GPT-5 nano has the lower combined listed price. |
| Generation speedtokens per second | GPT-5 nano137 tok/s | Mistral Large 348 tok/s | GPT-5 nano has the higher measured throughput. |
| First-answer latencyseconds to first token | GPT-5 nano83.30 s | Mistral Large 31.04 s | Mistral Large 3 reaches the first token sooner. |
| Context windowmaximum listed tokens | GPT-5 nano400K | Mistral Large 3128K | GPT-5 nano lists the larger context window. |
Benchmark Deep Dive
Agentic4 benchmarks
Coding2 benchmarks
Reasoning2 benchmarks
Knowledge6 benchmarks
| Benchmark | GPT-5 nano | Mistral Large 3 | Result |
|---|---|---|---|
| Artificial Analysis Intelligence IndexSource | — | 15.9% | Not comparable |
| AA-GPQA DiamondSource | — | 68.0% | Not comparable |
| AA-HLESource | — | 4.1% | Not comparable |
| AA-Omniscience IndexSource | — | -39.4% | Not comparable |
| AA-Omniscience AccuracySource | — | 24.1% | Not comparable |
| AA-Omniscience Hallucination RateSource | — | 83.7% | Not comparable |
Multimodal1 benchmarks
| Benchmark | GPT-5 nano | Mistral Large 3 | Result |
|---|---|---|---|
| AA-MMMU-ProSource | — | 55.7% | Not comparable |
Inst. Following1 benchmarks
| Benchmark | GPT-5 nano | Mistral Large 3 | Result |
|---|---|---|---|
| AA-IFBenchSource | — | 36.2% | Not comparable |
Frequently Asked Questions (3)
Can I compare GPT-5 nano and Mistral Large 3 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 nano and Mistral Large 3 today?
GPT-5 nano: $0.05 input / $0.40 output per 1M tokens Mistral Large 3: $0.50 input / $1.50 output per 1M tokens Both model pages still include creator, context window, reasoning mode, and other metadata while benchmark coverage fills in.
Self-host vs API cost
Estimates at 50,000 req/day · 1000 tokens/req average.