Compare models. Find the differences.
Add, remove, or change models in the table.
Benchmark snapshot
0 benchmarks in common.
4 models selected. 0 benchmarks in common.
Reported scores; test settings may differ.
| Benchmark | Google | Mistral AI | OpenAI | NVIDIA |
|---|---|---|---|---|
| Arena ELOHuman preference | 1,409 | Not in our dataset | 1,389 | 1,360 |
| GPQA DiamondScientific knowledge | 82.8% | 68.2% | Not in our dataset | Not in our dataset |
| HLEAcademic reasoning | 11.0% | Not in our dataset | Not in our dataset | 18.3% |
| MMLU ProMulti-task understanding | Not in our dataset | Not in our dataset | Not in our dataset | 83.7% |
| SimpleBenchCommonsense reasoning | 41.2% | Not in our dataset | 41.7% | Not in our dataset |
| AIME 2025Mathematics | 72.0% | 62.8% | Not in our dataset | Not in our dataset |
| AiderCode editing | 55.1% | Not in our dataset | Not in our dataset | Not in our dataset |
| SWE-Bench VerifiedAgentic coding | 60.4% | Not in our dataset | Not in our dataset | Not in our dataset |
| LiveCodeBenchCompetitive coding | 62.6% | 55.4% | Not in our dataset | Not in our dataset |
| Tau-BenchAgentic tool use | Not in our dataset | Not in our dataset | Not in our dataset | 62.8% |
| Terminal-BenchAgentic terminal | 16.9% | Not in our dataset | Not in our dataset | Not in our dataset |
| ARC-AGI-2Visual reasoning | 2.5% | 0.0% | Not in our dataset | Not in our dataset |
Pricing & context Published USD rates per 1M tokens
| Specification | Gemini 2.5 Flash Thinking | MistralAI Magistral Small Thinking | o1 Preview | Nemotron 3 Super 120B-A12B |
|---|---|---|---|---|
| Input | $0.3 | $0.5 | $15 | $0.3 |
| Output | $2.5 | $1.5 | $60 | $2.4 |
| Context window | 1.0M | 40K | 200K | 1.0M |
| Pricing details | Explore pricing → | Explore pricing → | Explore pricing → | Explore pricing → |
How to read this comparison
Each column keeps the exact model version you selected. Shared benchmarks are the intersection of their reported results; “all coverage” also shows where evidence is missing. Missing results never count as zero.
These are published benchmark scores, not a controlled head-to-head test. The available evidence does not establish matching evaluation settings, so we show no cross-model winner highlights or deltas. Composite quality scores are omitted because they can summarize different benchmark sets.
Scores and statistics are computed upstream. This page reads a fixed data snapshot; its date describes the snapshot, not the date of every measurement.