Model comparison
GPT-4.1 nano vs Mistral Large 3
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-4.1 nano #170 (Estimated); Mistral Large 3 #118 (Supported). Intervals and evidence labels describe ranking uncertainty, not a guarantee for a specific workload.
Evidence parity. GPT-4.1 nano and Mistral Large 3 share 16 comparable benchmark results. 0 of 8 categories are comparable. 5 results are unique to GPT-4.1 nano; 0 to Mistral Large 3.
Updated July 24, 2026- Shared results
- 16
- GPT-4.1 nano only
- 5
- Mistral Large 3 only
- 0
- Comparable categories
- 0 / 8
Benchmark data for GPT-4.1 nano and Mistral Large 3 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 Large 3 is priced at $0.50 input / $1.50 output per 1M tokens, versus $0.10 input / $0.40 output per 1M tokens for GPT-4.1 nano. GPT-4.1 nano has the larger context window at 1M, compared with 128K for Mistral Large 3.
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-4.1 nano | Δ | Mistral Large 3 |
|---|---|---|---|
| Knowledge | GPT-4.1 nano50.3 | MarginNo overlap | Mistral Large 3Not measured |
| Math | GPT-4.1 nano1.0 | MarginNo overlap | Mistral Large 3Not measured |
| Inst. Following | GPT-4.1 nano83.2 | MarginNo overlap | Mistral Large 3Not measured |
Operational comparison
Runtime and commercial metrics are compared only when both models have a complete sourced value.
| Metric | GPT-4.1 nano | Mistral Large 3 | Comparison |
|---|---|---|---|
| Input / output priceUSD per 1M tokens | GPT-4.1 nano$0.1 input / $0.4 output | Mistral Large 3$0.5 input / $1.5 output | GPT-4.1 nano has the lower combined listed price. |
| Generation speedtokens per second | GPT-4.1 nano181 tok/s | Mistral Large 348 tok/s | GPT-4.1 nano has the higher measured throughput. |
| First-answer latencyseconds to first token | GPT-4.1 nano0.63 s | Mistral Large 31.04 s | GPT-4.1 nano reaches the first token sooner. |
| Context windowmaximum listed tokens | GPT-4.1 nano1M | Mistral Large 3128K | GPT-4.1 nano lists the larger context window. |
Benchmark Deep Dive
Agentic4 benchmarks
Coding2 benchmarks
Reasoning2 benchmarks
Knowledge8 benchmarks
| Benchmark | GPT-4.1 nano | Mistral Large 3 | Result |
|---|---|---|---|
| MMLUSource | 80.1% | — | Not comparable |
| GPQASource | 50.3% | — | Not comparable |
| Artificial Analysis Intelligence IndexSource | 9.6% | 15.9% | Mistral Large 3 leads |
| AA-GPQA DiamondSource | 51.2% | 68.0% | Mistral Large 3 leads |
| AA-HLESource | 3.9% | 4.1% | Mistral Large 3 leads |
| AA-Omniscience IndexSource | -56.4% | -39.4% | Mistral Large 3 leads |
| AA-Omniscience AccuracySource | 13.3% | 24.1% | Mistral Large 3 leads |
| AA-Omniscience Hallucination RateSource | 80.4% | 83.7% | GPT-4.1 nano leads |
Math1 benchmarks
| Benchmark | GPT-4.1 nano | Mistral Large 3 | Result |
|---|---|---|---|
| FrontierMath v2 (Tiers 1-3)Source | 1.034% | — | Not comparable |
Multimodal2 benchmarks
Frequently Asked Questions (3)
Can I compare GPT-4.1 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-4.1 nano and Mistral Large 3 today?
GPT-4.1 nano: $0.10 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.