Model comparison
GPT-6 Luna vs MiMo-V2-Flash
GPT-6 Luna is the stronger model overall, scoring 45.1 to 40.8 on the Noometry Index.
Last verified . 14 shared benchmarks.
Summary
- They share 14 benchmarks with published results for both. GPT-6 Luna scores higher in 5 categories and MiMo-V2-Flash in 3 categories; 5 gaps are clear of the uncertainty.
- The widest gap is in coding, where GPT-6 Luna leads 54.7 to 35.8.
- MiMo-V2-Flash is cheaper at $0.14 / $0.28 per million input/output tokens, against $0.10 / $0.50 for GPT-6 Luna.
- GPT-6 Luna accepts more context: 1.05M tokens versus 262K.
- MiMo-V2-Flash has downloadable open weights; the other is API-only.
Side by side
| GPT-6 Luna | MiMo-V2-Flash | |
|---|---|---|
| Provider | OpenAI | Xiaomi |
| Noometry Index | 45.1 | 40.8 |
| Released | 2026-09-22 | 2025-12-16 |
| Weights | Proprietary | Open |
| Context window | 1.05M | 262K |
| Max output | 128K | 66K |
| Input $ / M tokens | $0.10 | $0.14 |
| Output $ / M tokens | $0.50 | $0.28 |
| Results tracked | 18 | 21 |
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Category by category
Coding GPT-6 Luna leads
GPT-6 Luna: 54.7 (#24), MiMo-V2-Flash: 35.8 (#205)
| Benchmark | GPT-6 Luna | MiMo-V2-Flash |
|---|---|---|
| LMArena WebDev | 1583 | 1330 |
| LMArena Coding | 1448 | 1443 |
| DeepSWE | 66.6% | — |
| FrontierCode | 42.4% | — |
| SciCode | — | 25.9% |
| ALE-Bench | — | 737.95 |
Reasoning GPT-6 Luna leads
GPT-6 Luna: 31.7 (#68), MiMo-V2-Flash: 24.1 (#155)
| Benchmark | GPT-6 Luna | MiMo-V2-Flash |
|---|---|---|
| LMArena Hard Prompts | 1415 | 1420 |
| NYT Connections (extended) | 68.7% | — |
| CritPt | — | 0% |
Math Too close to call
GPT-6 Luna: 35.6 (#140), MiMo-V2-Flash: 35.6 (#141)
| Benchmark | GPT-6 Luna | MiMo-V2-Flash |
|---|---|---|
| LMArena Math | 1396 | 1396 |
Knowledge GPT-6 Luna leads
GPT-6 Luna: 40.1 (#110), MiMo-V2-Flash: 39.1 (#126)
| Benchmark | GPT-6 Luna | MiMo-V2-Flash |
|---|---|---|
| LMArena Expert | 1458 | 1425 |
Multimodal Not comparable
GPT-6 Luna: 42.0 (#27), MiMo-V2-Flash: —
| Benchmark | GPT-6 Luna | MiMo-V2-Flash |
|---|---|---|
| Furniture Assembly | 44.2% | — |
Multilingual Too close to call
GPT-6 Luna: 51.0 (#111), MiMo-V2-Flash: 51.1 (#109)
| Benchmark | GPT-6 Luna | MiMo-V2-Flash |
|---|---|---|
| LMArena Non-English | 1390 | 1391 |
| LMArena Chinese | 1425 | 1463 |
| LMArena Russian | 1392 | 1387 |
| LMArena Spanish | 1416 | 1420 |
| LMArena French | — | 1429 |
| LMArena German | — | 1395 |
| LMArena Japanese | — | 1324 |
| LMArena Korean | — | 1358 |
Instruction Following GPT-6 Luna leads
GPT-6 Luna: 74.7 (#85), MiMo-V2-Flash: 73.7 (#115)
| Benchmark | GPT-6 Luna | MiMo-V2-Flash |
|---|---|---|
| LMArena Instruction Following | 1414 | 1392 |
Long Context Too close to call
GPT-6 Luna: 43.3 (#95), MiMo-V2-Flash: 43.0 (#106)
| Benchmark | GPT-6 Luna | MiMo-V2-Flash |
|---|---|---|
| LMArena Longer Query | 1417 | 1409 |
Writing & Preference MiMo-V2-Flash leads
GPT-6 Luna: 58.4 (#115), MiMo-V2-Flash: 59.9 (#101)
| Benchmark | GPT-6 Luna | MiMo-V2-Flash |
|---|---|---|
| LMArena Text | 1392 | 1411 |
| LMArena Creative Writing | 1357 | 1375 |
| LMArena Multi-Turn | 1400 | 1404 |
Frequently asked questions
Is GPT-6 Luna better than MiMo-V2-Flash?
GPT-6 Luna is the stronger model overall, scoring 45.1 to 40.8 on the Noometry Index.
Which is cheaper, GPT-6 Luna or MiMo-V2-Flash?
MiMo-V2-Flash is cheaper. It lists at $0.14 per million input tokens and $0.28 per million output tokens; GPT-6 Luna lists at $0.10 and $0.50.
Is GPT-6 Luna or MiMo-V2-Flash better for coding?
GPT-6 Luna scores higher on coding benchmarks: 54.7 versus 35.8 in the Noometry coding category.
Which has the bigger context window?
GPT-6 Luna does, with 1.05M tokens against 262K.
How many benchmarks do GPT-6 Luna and MiMo-V2-Flash share?
14 benchmarks have published results for both models. GPT-6 Luna has 18 scored results on Noometry and MiMo-V2-Flash has 21.