Model comparison
GPT-6 Astra vs MiMo-V2-Omni
GPT-6 Astra is the stronger model overall, scoring 70.3 to 42.9 on the Noometry Index. MiMo-V2-Omni costs 114× less per token, which makes it the better buy when GPT-6 Astra's lead doesn't matter for your workload.
Last verified . 15 shared benchmarks.
Summary
- They share 15 benchmarks with published results for both. GPT-6 Astra scores higher in 9 categories and MiMo-V2-Omni in 0 categories; 8 gaps are clear of the uncertainty.
- The widest gap is in math, where GPT-6 Astra leads 93.4 to 36.4.
- MiMo-V2-Omni is cheaper at $0.14 / $0.28 per million input/output tokens, against $10 / $50 for GPT-6 Astra.
- GPT-6 Astra accepts more context: 1.05M tokens versus 262K.
Side by side
| GPT-6 Astra | MiMo-V2-Omni | |
|---|---|---|
| Provider | OpenAI | Xiaomi |
| Noometry Index | 70.3 | 42.9 |
| Released | 2026-09-03 | 2026-03-18 |
| Weights | Proprietary | Proprietary |
| Context window | 1.05M | 262K |
| Max output | 128K | 131K |
| Input $ / M tokens | $10 | $0.14 |
| Output $ / M tokens | $50 | $0.28 |
| Results tracked | 51 | 18 |
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Category by category
Coding GPT-6 Astra leads
GPT-6 Astra: 70.5 (#3), MiMo-V2-Omni: 42.7 (#87)
| Benchmark | GPT-6 Astra | MiMo-V2-Omni |
|---|---|---|
| LMArena Coding | 1488 | 1467 |
| DeepSWE | 74.1% | — |
| FrontierCode | 53.3% | — |
| LMArena WebDev | 1792 | — |
| FrontierSWE | 65.5% | — |
| SciCode | 56.5% | — |
| WeirdML | 93.6% | — |
| MirrorCode | 46.7% | — |
| ALE-Bench | 2,951 | — |
Agentic & Tool Use Not comparable
GPT-6 Astra: 52.3 (#3), MiMo-V2-Omni: —
| Benchmark | GPT-6 Astra | MiMo-V2-Omni |
|---|---|---|
| APEX-Agents | 64.7% | — |
| Remote Labor Index | 20.8% | — |
| BALROG | 68.3% | — |
| Vending-Bench 2 | 15,515 | — |
Reasoning GPT-6 Astra leads
GPT-6 Astra: 85.1 (#1), MiMo-V2-Omni: 28.6 (#86)
| Benchmark | GPT-6 Astra | MiMo-V2-Omni |
|---|---|---|
| LMArena Hard Prompts | 1464 | 1445 |
| ARC-AGI-2 | 95% | — |
| NYT Connections (extended) | 98.1% | — |
| ARC-AGI-1 | 98.5% | — |
| CritPt | 31.7% | — |
| Chess Puzzles | 72% | — |
| EBR-Bench | 76.2% | — |
| Mystery Game Puzzles | 84% | — |
| DTBench | 97.3% | — |
| LMCA | 64.4% | — |
| Bench to the Future 3 | 0.14 | — |
| Epoch Capabilities Index | 166.6 | — |
Math GPT-6 Astra leads
GPT-6 Astra: 93.4 (#1), MiMo-V2-Omni: 36.4 (#112)
| Benchmark | GPT-6 Astra | MiMo-V2-Omni |
|---|---|---|
| LMArena Math | 1463 | 1432 |
| FrontierMath (Tiers 1-3) | 93.7% | — |
| FrontierMath Tier 4 | 97.6% | — |
| OTIS Mock AIME 2024-2025 | 100% | — |
| ProofBench | 99% | — |
| FrontierMath Erdős | 2.9% | — |
Knowledge GPT-6 Astra leads
GPT-6 Astra: 75.3 (#1), MiMo-V2-Omni: 39.9 (#114)
| Benchmark | GPT-6 Astra | MiMo-V2-Omni |
|---|---|---|
| LMArena Expert | 1486 | 1449 |
| GPQA Diamond | 95.8% | — |
| Humanity's Last Exam | 54.8% | — |
| SimpleQA Verified | 75.6% | — |
| Vectara Hallucination Rate | 8.7% | — |
Multimodal GPT-6 Astra leads
GPT-6 Astra: 55.1 (#3), MiMo-V2-Omni: 37.9 (#62)
| Benchmark | GPT-6 Astra | MiMo-V2-Omni |
|---|---|---|
| LMArena Vision | 1280 | 1228 |
| Blueprint-Bench 2 | 49.7% | — |
| Furniture Assembly | 80% | — |
| LMArena Document | 1468 | — |
Multilingual GPT-6 Astra leads
GPT-6 Astra: 54.0 (#53), MiMo-V2-Omni: 52.0 (#97)
| Benchmark | GPT-6 Astra | MiMo-V2-Omni |
|---|---|---|
| LMArena Non-English | 1431 | 1404 |
| LMArena Chinese | 1495 | 1469 |
| LMArena French | 1467 | 1448 |
| LMArena Russian | 1434 | 1412 |
| LMArena Spanish | 1412 | 1432 |
| LMArena German | — | 1398 |
| LMArena Japanese | — | 1318 |
| LMArena Korean | — | 1355 |
Instruction Following GPT-6 Astra leads
GPT-6 Astra: 76.6 (#37), MiMo-V2-Omni: 75.4 (#62)
| Benchmark | GPT-6 Astra | MiMo-V2-Omni |
|---|---|---|
| LMArena Instruction Following | 1454 | 1428 |
Long Context Too close to call
GPT-6 Astra: 44.7 (#57), MiMo-V2-Omni: 44.1 (#72)
| Benchmark | GPT-6 Astra | MiMo-V2-Omni |
|---|---|---|
| LMArena Longer Query | 1460 | 1442 |
Writing & Preference GPT-6 Astra leads
GPT-6 Astra: 75.7 (#7), MiMo-V2-Omni: 61.6 (#83)
| Benchmark | GPT-6 Astra | MiMo-V2-Omni |
|---|---|---|
| LMArena Text | 1443 | 1424 |
| LMArena Creative Writing | 1423 | 1393 |
| LMArena Multi-Turn | 1457 | 1446 |
| EQ-Bench Creative Writing | 2173 | — |
Frequently asked questions
Is GPT-6 Astra better than MiMo-V2-Omni?
GPT-6 Astra is the stronger model overall, scoring 70.3 to 42.9 on the Noometry Index. MiMo-V2-Omni costs 114× less per token, which makes it the better buy when GPT-6 Astra's lead doesn't matter for your workload.
Which is cheaper, GPT-6 Astra or MiMo-V2-Omni?
MiMo-V2-Omni is cheaper. It lists at $0.14 per million input tokens and $0.28 per million output tokens; GPT-6 Astra lists at $10 and $50.
Is GPT-6 Astra or MiMo-V2-Omni better for coding?
GPT-6 Astra scores higher on coding benchmarks: 70.5 versus 42.7 in the Noometry coding category.
Which has the bigger context window?
GPT-6 Astra does, with 1.05M tokens against 262K.
How many benchmarks do GPT-6 Astra and MiMo-V2-Omni share?
15 benchmarks have published results for both models. GPT-6 Astra has 51 scored results on Noometry and MiMo-V2-Omni has 18.