Model comparison
GPT-5-Codex vs MiMo-V2-Omni
MiMo-V2-Omni is the stronger model overall, scoring 42.9 to 37.3 on the Noometry Index.
Last verified . 0 shared benchmarks.
Summary
- MiMo-V2-Omni is cheaper at $0.14 / $0.28 per million input/output tokens, against $1.25 / $10 for GPT-5-Codex.
- GPT-5-Codex accepts more context: 400K tokens versus 262K.
Side by side
| GPT-5-Codex | MiMo-V2-Omni | |
|---|---|---|
| Provider | OpenAI | Xiaomi |
| Noometry Index | 37.3 | 42.9 |
| Released | 2025-09-15 | 2026-03-18 |
| Weights | Proprietary | Proprietary |
| Context window | 400K | 262K |
| Max output | 128K | 131K |
| Input $ / M tokens | $1.25 | $0.14 |
| Output $ / M tokens | $10 | $0.28 |
| Results tracked | 3 | 18 |
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Category by category
Coding Too close to call
GPT-5-Codex: 41.9 (#100), MiMo-V2-Omni: 42.7 (#87)
| Benchmark | GPT-5-Codex | MiMo-V2-Omni |
|---|---|---|
| WeirdML | 54.5% | — |
| LMArena Coding | — | 1467 |
Agentic & Tool Use Not comparable
GPT-5-Codex: 30.8 (#66), MiMo-V2-Omni: —
| Benchmark | GPT-5-Codex | MiMo-V2-Omni |
|---|---|---|
| Terminal-Bench | 44.3% | — |
Reasoning GPT-5-Codex leads
GPT-5-Codex: 30.0 (#80), MiMo-V2-Omni: 28.6 (#86)
| Benchmark | GPT-5-Codex | MiMo-V2-Omni |
|---|---|---|
| Kagi LLM Benchmark | 70.3% | — |
| LMArena Hard Prompts | — | 1445 |
Math Not comparable
GPT-5-Codex: —, MiMo-V2-Omni: 36.4 (#112)
| Benchmark | GPT-5-Codex | MiMo-V2-Omni |
|---|---|---|
| LMArena Math | — | 1432 |
Knowledge Not comparable
GPT-5-Codex: —, MiMo-V2-Omni: 39.9 (#114)
| Benchmark | GPT-5-Codex | MiMo-V2-Omni |
|---|---|---|
| LMArena Expert | — | 1449 |
Multimodal Not comparable
GPT-5-Codex: —, MiMo-V2-Omni: 37.9 (#62)
| Benchmark | GPT-5-Codex | MiMo-V2-Omni |
|---|---|---|
| LMArena Vision | — | 1228 |
Multilingual Not comparable
GPT-5-Codex: —, MiMo-V2-Omni: 52.0 (#97)
| Benchmark | GPT-5-Codex | MiMo-V2-Omni |
|---|---|---|
| LMArena Non-English | — | 1404 |
| LMArena Chinese | — | 1469 |
| LMArena French | — | 1448 |
| LMArena German | — | 1398 |
| LMArena Japanese | — | 1318 |
| LMArena Korean | — | 1355 |
| LMArena Russian | — | 1412 |
| LMArena Spanish | — | 1432 |
Instruction Following Not comparable
GPT-5-Codex: —, MiMo-V2-Omni: 75.4 (#62)
| Benchmark | GPT-5-Codex | MiMo-V2-Omni |
|---|---|---|
| LMArena Instruction Following | — | 1428 |
Long Context Not comparable
GPT-5-Codex: —, MiMo-V2-Omni: 44.1 (#72)
| Benchmark | GPT-5-Codex | MiMo-V2-Omni |
|---|---|---|
| LMArena Longer Query | — | 1442 |
Writing & Preference Not comparable
GPT-5-Codex: —, MiMo-V2-Omni: 61.6 (#83)
| Benchmark | GPT-5-Codex | MiMo-V2-Omni |
|---|---|---|
| LMArena Text | — | 1424 |
| LMArena Creative Writing | — | 1393 |
| LMArena Multi-Turn | — | 1446 |
Frequently asked questions
Is GPT-5-Codex better than MiMo-V2-Omni?
MiMo-V2-Omni is the stronger model overall, scoring 42.9 to 37.3 on the Noometry Index.
Which is cheaper, GPT-5-Codex 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-5-Codex lists at $1.25 and $10.
Is GPT-5-Codex or MiMo-V2-Omni better for coding?
They score almost the same on coding (41.9 vs 42.7); test both on your own repository before choosing.
Which has the bigger context window?
GPT-5-Codex does, with 400K tokens against 262K.
How many benchmarks do GPT-5-Codex and MiMo-V2-Omni share?
0 benchmarks have published results for both models. GPT-5-Codex has 3 scored results on Noometry and MiMo-V2-Omni has 18.