Compare models. Find the differences.
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Benchmark snapshot
1 benchmarks in common.
4 models selected. 1 benchmarks in common.
Reported scores; test settings may differ.
| Benchmark | Anthropic | MiniMax | Qwen | xAI |
|---|---|---|---|---|
| Arena ELOHuman preference | 1,425 | 1,415 | 1,436 | 1,411 |
| LiveBench 1.0General reasoning | 72.1% | Not in our dataset | 75.3% | Not in our dataset |
| GPQA DiamondScientific knowledge | Not in our dataset | 87.0% | Not in our dataset | 87.5% |
| HLEAcademic reasoning | 30.1% | 28.0% | Not in our dataset | 25.4% |
| MMLU ProMulti-task understanding | Not in our dataset | 81.9% | Not in our dataset | 86.6% |
| SimpleBenchCommonsense reasoning | Not in our dataset | Not in our dataset | 60.2% | 60.5% |
| AIME 2025Mathematics | Not in our dataset | Not in our dataset | Not in our dataset | 91.7% |
| AiderCode editing | Not in our dataset | Not in our dataset | Not in our dataset | 79.6% |
| SWE-Bench VerifiedAgentic coding | Not in our dataset | 72.2% | Not in our dataset | Not in our dataset |
| Tau-BenchAgentic tool use | Not in our dataset | 84.9% | Not in our dataset | 76.5% |
| Terminal-BenchAgentic terminal | Not in our dataset | Not in our dataset | Not in our dataset | 23.1% |
| ARC-AGI-2Visual reasoning | 61.3% | Not in our dataset | 42.4% | 16.0% |
Pricing & context Published USD rates per 1M tokens
| Specification | Claude Haiku 5.5 Thinking | M2 M2.7 | 3.8 27B Thinking | Grok 4 |
|---|---|---|---|---|
| Input | $0.1 | $0.255 | $0.15 | $3 |
| Output | $0.5 | $1.02 | $1.875 | $15 |
| Context window | 1.0M | 205K | 1.0M | 256K |
| 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.