Model comparison
GPT-6.1 Sol vs MiMo-V2-Pro
GPT-6.1 Sol is the stronger model overall, scoring 65.6 to 43.0 on the Noometry Index. MiMo-V2-Pro costs 7.4× less per token, which makes it the better buy when GPT-6.1 Sol's lead doesn't matter for your workload.
Last verified . 14 shared benchmarks.
Summary
- They share 14 benchmarks with published results for both. GPT-6.1 Sol scores higher in 8 categories and MiMo-V2-Pro in 0 categories; 7 gaps are clear of the uncertainty.
- The widest gap is in reasoning, where GPT-6.1 Sol leads 81.9 to 22.1.
- The biggest single-benchmark swing is NYT Connections (extended): 95.5% for GPT-6.1 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-6.1 Sol.
- GPT-6.1 Sol accepts more context: 1.05M tokens versus 1.05M.
Side by side
| GPT-6.1 Sol | MiMo-V2-Pro | |
|---|---|---|
| Provider | OpenAI | Xiaomi |
| Noometry Index | 65.6 | 43.0 |
| Released | 2026-09-29 | 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 | 34 | 23 |
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Category by category
Coding GPT-6.1 Sol leads
GPT-6.1 Sol: 63.2 (#8), MiMo-V2-Pro: 43.8 (#83)
| Benchmark | GPT-6.1 Sol | MiMo-V2-Pro |
|---|---|---|
| LMArena WebDev | 1755 | 1433 |
| LMArena Coding | 1487 | 1476 |
| DeepSWE | 75.2% | — |
| FrontierCode | 50.2% | — |
| SciCode | 55.8% | — |
| ALE-Bench | — | 785.17 |
Agentic & Tool Use Not comparable
GPT-6.1 Sol: 39.6 (#26), MiMo-V2-Pro: —
| Benchmark | GPT-6.1 Sol | MiMo-V2-Pro |
|---|---|---|
| APEX-Agents | 60% | — |
| GDP.pdf | 32% | — |
Reasoning GPT-6.1 Sol leads
GPT-6.1 Sol: 81.9 (#2), MiMo-V2-Pro: 22.1 (#206)
| Benchmark | GPT-6.1 Sol | MiMo-V2-Pro |
|---|---|---|
| NYT Connections (extended) | 95.5% | 25.8% |
| LMArena Hard Prompts | 1466 | 1457 |
| ARC-AGI-2 | 94.2% | — |
| ARC-AGI-1 | 98.5% | — |
| CritPt | 31.7% | — |
| Chess Puzzles | 61% | — |
| Thematic Generalization | — | 45.9% |
| EBR-Bench | 54.3% | — |
| Mystery Game Puzzles | 80% | — |
| Epoch Capabilities Index | 166.09 | — |
Math GPT-6.1 Sol leads
GPT-6.1 Sol: 93.7 (#1), MiMo-V2-Pro: 39.5 (#102)
| Benchmark | GPT-6.1 Sol | MiMo-V2-Pro |
|---|---|---|
| LMArena Math | 1464 | 1447 |
| FrontierMath (Tiers 1-3) | 93.7% | — |
| FrontierMath Tier 4 | 100% | — |
| OTIS Mock AIME 2024-2025 | 100% | — |
| ProofBench | 99% | — |
Knowledge GPT-6.1 Sol leads
GPT-6.1 Sol: 71.8 (#4), MiMo-V2-Pro: 41.4 (#111)
| Benchmark | GPT-6.1 Sol | MiMo-V2-Pro |
|---|---|---|
| LMArena Expert | 1502 | 1478 |
| GPQA Diamond | 95.4% | — |
| SimpleQA Verified | 73.9% | — |
Multimodal Not comparable
GPT-6.1 Sol: 52.7 (#5), MiMo-V2-Pro: —
| Benchmark | GPT-6.1 Sol | MiMo-V2-Pro |
|---|---|---|
| LMArena Vision | 1288 | — |
| Furniture Assembly | 80% | — |
Multilingual GPT-6.1 Sol leads
GPT-6.1 Sol: 54.3 (#46), MiMo-V2-Pro: 52.7 (#81)
| Benchmark | GPT-6.1 Sol | MiMo-V2-Pro |
|---|---|---|
| LMArena Non-English | 1438 | 1416 |
| LMArena Chinese | 1477 | 1456 |
| LMArena Russian | 1455 | 1427 |
| LMArena French | — | 1469 |
| LMArena German | — | 1417 |
| LMArena Japanese | — | 1366 |
| LMArena Korean | — | 1400 |
| LMArena Spanish | — | 1457 |
Instruction Following GPT-6.1 Sol leads
GPT-6.1 Sol: 77.0 (#29), MiMo-V2-Pro: 76.0 (#49)
| Benchmark | GPT-6.1 Sol | MiMo-V2-Pro |
|---|---|---|
| LMArena Instruction Following | 1468 | 1445 |
Long Context GPT-6.1 Sol leads
GPT-6.1 Sol: 44.9 (#54), MiMo-V2-Pro: 41.5 (#138)
| Benchmark | GPT-6.1 Sol | MiMo-V2-Pro |
|---|---|---|
| LMArena Longer Query | 1465 | 1455 |
| CL-bench | — | 15.7% |
| CL-bench Life | — | 6.9% |
Writing & Preference Too close to call
GPT-6.1 Sol: 63.6 (#63), MiMo-V2-Pro: 62.8 (#70)
| Benchmark | GPT-6.1 Sol | MiMo-V2-Pro |
|---|---|---|
| LMArena Text | 1447 | 1436 |
| LMArena Creative Writing | 1432 | 1415 |
| LMArena Multi-Turn | 1449 | 1456 |
Frequently asked questions
Is GPT-6.1 Sol better than MiMo-V2-Pro?
GPT-6.1 Sol is the stronger model overall, scoring 65.6 to 43.0 on the Noometry Index. MiMo-V2-Pro costs 7.4× less per token, which makes it the better buy when GPT-6.1 Sol's lead doesn't matter for your workload.
Which is cheaper, GPT-6.1 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-6.1 Sol lists at $2 and $10.
Is GPT-6.1 Sol or MiMo-V2-Pro better for coding?
GPT-6.1 Sol scores higher on coding benchmarks: 63.2 versus 43.8 in the Noometry coding category.
Which has the bigger context window?
GPT-6.1 Sol does, with 1.05M tokens against 1.05M.
How many benchmarks do GPT-6.1 Sol and MiMo-V2-Pro share?
14 benchmarks have published results for both models. GPT-6.1 Sol has 34 scored results on Noometry and MiMo-V2-Pro has 23.