Model comparison
GPT-6 Sol vs MiMo-V2-Pro
GPT-6 Sol is the stronger model overall, scoring 61.8 to 43.0 on the Noometry Index. MiMo-V2-Pro costs 7.4× less per token, which makes it the better buy when GPT-6 Sol's lead doesn't matter for your workload.
Last verified . 20 shared benchmarks.
Summary
- They share 20 benchmarks with published results for both. GPT-6 Sol scores higher in 6 categories and MiMo-V2-Pro in 2 categories; 8 gaps are clear of the uncertainty.
- The widest gap is in reasoning, where GPT-6 Sol leads 74.0 to 22.1.
- The biggest single-benchmark swing is NYT Connections (extended): 90.1% for GPT-6 Sol and 25.8% for MiMo-V2-Pro.
- MiMo-V2-Pro is cheaper at $0.43 / $0.87 per million input/output tokens, against $2 / $10 for GPT-6 Sol.
- GPT-6 Sol accepts more context: 1.05M tokens versus 1.05M.
Side by side
| GPT-6 Sol | MiMo-V2-Pro | |
|---|---|---|
| Provider | OpenAI | Xiaomi |
| Noometry Index | 61.8 | 43.0 |
| Released | 2026-09-22 | 2026-03-18 |
| Weights | Proprietary | Proprietary |
| Context window | 1.05M | 1.05M |
| Max output | 128K | 131K |
| Input $ / M tokens | $2 | $0.43 |
| Output $ / M tokens | $10 | $0.87 |
| Results tracked | 45 | 23 |
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Category by category
Coding GPT-6 Sol leads
GPT-6 Sol: 60.1 (#11), MiMo-V2-Pro: 43.8 (#83)
| Benchmark | GPT-6 Sol | MiMo-V2-Pro |
|---|---|---|
| LMArena WebDev | 1688 | 1433 |
| LMArena Coding | 1447 | 1476 |
| ALE-Bench | 2,462 | 785.17 |
| DeepSWE | 68.8% | — |
| FrontierCode | 49.3% | — |
| SciCode | 57.6% | — |
Agentic & Tool Use Not comparable
GPT-6 Sol: 37.2 (#36), MiMo-V2-Pro: —
| Benchmark | GPT-6 Sol | MiMo-V2-Pro |
|---|---|---|
| APEX-Agents | 54.3% | — |
| GDP.pdf | 26.4% | — |
| Vending-Bench 2 | 14,428 | — |
Reasoning GPT-6 Sol leads
GPT-6 Sol: 74.0 (#9), MiMo-V2-Pro: 22.1 (#206)
| Benchmark | GPT-6 Sol | MiMo-V2-Pro |
|---|---|---|
| NYT Connections (extended) | 90.1% | 25.8% |
| LMArena Hard Prompts | 1418 | 1457 |
| ARC-AGI-2 | 89.6% | — |
| ARC-AGI-1 | 95.5% | — |
| CritPt | 30.9% | — |
| Thematic Generalization | — | 45.9% |
| EBR-Bench | 53.3% | — |
| Mystery Game Puzzles | 56% | — |
| DTBench | 97.3% | — |
| LMCA | 59.1% | — |
| Epoch Capabilities Index | 162.72 | — |
Math GPT-6 Sol leads
GPT-6 Sol: 87.2 (#7), MiMo-V2-Pro: 39.5 (#102)
| Benchmark | GPT-6 Sol | MiMo-V2-Pro |
|---|---|---|
| LMArena Math | 1402 | 1447 |
| FrontierMath (Tiers 1-3) | 89.8% | — |
| FrontierMath Tier 4 | 90% | — |
| OTIS Mock AIME 2024-2025 | 100% | — |
| ProofBench | 83% | — |
Knowledge GPT-6 Sol leads
GPT-6 Sol: 64.8 (#15), MiMo-V2-Pro: 41.4 (#111)
| Benchmark | GPT-6 Sol | MiMo-V2-Pro |
|---|---|---|
| LMArena Expert | 1439 | 1478 |
| GPQA Diamond | 94.3% | — |
| SimpleQA Verified | 60.7% | — |
| Vectara Hallucination Rate | 6.5% | — |
Multimodal Not comparable
GPT-6 Sol: 47.6 (#10), MiMo-V2-Pro: —
| Benchmark | GPT-6 Sol | MiMo-V2-Pro |
|---|---|---|
| LMArena Vision | 1245 | — |
| Blueprint-Bench 2 | 36.9% | — |
| Furniture Assembly | 58.3% | — |
Multilingual MiMo-V2-Pro leads
GPT-6 Sol: 50.5 (#118), MiMo-V2-Pro: 52.7 (#81)
| Benchmark | GPT-6 Sol | MiMo-V2-Pro |
|---|---|---|
| LMArena Non-English | 1385 | 1416 |
| LMArena Chinese | 1405 | 1456 |
| LMArena French | 1410 | 1469 |
| LMArena German | 1390 | 1417 |
| LMArena Japanese | 1385 | 1366 |
| LMArena Korean | 1341 | 1400 |
| LMArena Russian | 1401 | 1427 |
| LMArena Spanish | 1384 | 1457 |
Instruction Following MiMo-V2-Pro leads
GPT-6 Sol: 74.5 (#94), MiMo-V2-Pro: 76.0 (#49)
| Benchmark | GPT-6 Sol | MiMo-V2-Pro |
|---|---|---|
| LMArena Instruction Following | 1412 | 1445 |
Long Context GPT-6 Sol leads
GPT-6 Sol: 43.1 (#108), MiMo-V2-Pro: 41.5 (#138)
| Benchmark | GPT-6 Sol | MiMo-V2-Pro |
|---|---|---|
| LMArena Longer Query | 1411 | 1455 |
| CL-bench | — | 15.7% |
| CL-bench Life | — | 6.9% |
Writing & Preference GPT-6 Sol leads
GPT-6 Sol: 71.9 (#18), MiMo-V2-Pro: 62.8 (#70)
| Benchmark | GPT-6 Sol | MiMo-V2-Pro |
|---|---|---|
| LMArena Text | 1395 | 1436 |
| LMArena Creative Writing | 1378 | 1415 |
| LMArena Multi-Turn | 1412 | 1456 |
| EQ-Bench Creative Writing | 2125 | — |
Frequently asked questions
Is GPT-6 Sol better than MiMo-V2-Pro?
GPT-6 Sol is the stronger model overall, scoring 61.8 to 43.0 on the Noometry Index. MiMo-V2-Pro costs 7.4× less per token, which makes it the better buy when GPT-6 Sol's lead doesn't matter for your workload.
Which is cheaper, GPT-6 Sol or MiMo-V2-Pro?
MiMo-V2-Pro is cheaper. It lists at $0.43 per million input tokens and $0.87 per million output tokens; GPT-6 Sol lists at $2 and $10.
Is GPT-6 Sol or MiMo-V2-Pro better for coding?
GPT-6 Sol scores higher on coding benchmarks: 60.1 versus 43.8 in the Noometry coding category.
Which has the bigger context window?
GPT-6 Sol does, with 1.05M tokens against 1.05M.
How many benchmarks do GPT-6 Sol and MiMo-V2-Pro share?
20 benchmarks have published results for both models. GPT-6 Sol has 45 scored results on Noometry and MiMo-V2-Pro has 23.