# GPT-5.6 Terra vs MiMo-V2-Flash

> GPT-5.6 Terra is the stronger model overall, scoring 59.1 to 40.8 on the Noometry Index. MiMo-V2-Flash costs 26× less per token, which makes it the better buy when GPT-5.6 Terra's lead doesn't matter for your workload.

- Canonical page: https://noometry.com/compare/gpt-5-6-terra-vs-mimo-v2-flash
- Last updated: 2026-10-10
- Shared benchmarks: 21

## Summary

- They share 21 benchmarks with published results for both. GPT-5.6 Terra scores higher in 8 categories and MiMo-V2-Flash in 0 categories; 8 gaps are clear of the uncertainty.
- The widest gap is in math, where GPT-5.6 Terra leads 81.5 to 35.6.
- The biggest single-benchmark swing is CritPt: 30% for GPT-5.6 Terra and 0% for MiMo-V2-Flash.
- MiMo-V2-Flash is cheaper at $0.14 / $0.28 per million input/output tokens, against $2 / $12 for GPT-5.6 Terra.
- GPT-5.6 Terra accepts more context: 1.05M tokens versus 262K.
- MiMo-V2-Flash has downloadable open weights; the other is API-only.

## Snapshot

| | GPT-5.6 Terra | MiMo-V2-Flash |
|---|---|---|
| Provider | OpenAI | Xiaomi |
| Noometry Index | 59.1 | 40.8 |
| Rank | 15 | 137 |
| Context | 1.05M | 262K |
| Input $/M | $2 | $0.14 |
| Output $/M | $12 | $0.28 |
| Weights | Proprietary | Open |

## Coding

- GPT-5.6 Terra: 57.1 (#16)
- MiMo-V2-Flash: 35.8 (#205)

| Benchmark | GPT-5.6 Terra | MiMo-V2-Flash |
|---|---|---|
| LMArena WebDev | 1520 | 1330 |
| SciCode | 55% | 25.9% |
| LMArena Coding | 1484 | 1443 |
| ALE-Bench | 1,951 | 737.95 |
| DeepSWE | 69.6% | — |
| FrontierCode | 41.3% | — |
| CursorBench | 41.3% | — |
| WeirdML | 78.3% | — |

## Agentic & Tool Use

- GPT-5.6 Terra: 40.2 (#23)
- MiMo-V2-Flash: —

| Benchmark | GPT-5.6 Terra | MiMo-V2-Flash |
|---|---|---|
| APEX-Agents | 58.2% | — |
| BALROG | 53.2% | — |
| GDP.pdf | 24.7% | — |
| Vending-Bench 2 | 7,343 | — |

## Reasoning

- GPT-5.6 Terra: 60.6 (#19)
- MiMo-V2-Flash: 24.1 (#155)

| Benchmark | GPT-5.6 Terra | MiMo-V2-Flash |
|---|---|---|
| CritPt | 30% | 0% |
| LMArena Hard Prompts | 1467 | 1420 |
| ARC-AGI-2 | 83.9% | — |
| SimpleBench | 48.9% | — |
| Kagi LLM Benchmark | 51.3% | — |
| NYT Connections (extended) | 78.4% | — |
| ARC-AGI-1 | 96.5% | — |
| Chess Puzzles | 54% | — |
| Mystery Game Puzzles | 35% | — |
| DTBench | 93.3% | — |
| LMCA | 55% | — |
| Surface Evolver Bench | 83.8% | — |
| Epoch Capabilities Index | 159.31 | — |

## Math

- GPT-5.6 Terra: 81.5 (#10)
- MiMo-V2-Flash: 35.6 (#141)

| Benchmark | GPT-5.6 Terra | MiMo-V2-Flash |
|---|---|---|
| LMArena Math | 1463 | 1396 |
| FrontierMath (Tiers 1-3) | 86% | — |
| FrontierMath Tier 4 | 70.7% | — |
| OTIS Mock AIME 2024-2025 | 99.7% | — |
| ProofBench | 74% | — |

## Knowledge

- GPT-5.6 Terra: 61.3 (#27)
- MiMo-V2-Flash: 39.1 (#126)

| Benchmark | GPT-5.6 Terra | MiMo-V2-Flash |
|---|---|---|
| LMArena Expert | 1492 | 1425 |
| GPQA Diamond | 93.3% | — |
| SimpleQA Verified | 43.2% | — |

## Multimodal

- GPT-5.6 Terra: 47.5 (#10)
- MiMo-V2-Flash: —

| Benchmark | GPT-5.6 Terra | MiMo-V2-Flash |
|---|---|---|
| LMArena Vision | 1271 | — |
| Blueprint-Bench 2 | 30.8% | — |
| Furniture Assembly | 54.2% | — |
| LMArena Document | 1472 | — |

## Multilingual

- GPT-5.6 Terra: 54.5 (#42)
- MiMo-V2-Flash: 51.1 (#109)

| Benchmark | GPT-5.6 Terra | MiMo-V2-Flash |
|---|---|---|
| LMArena Non-English | 1439 | 1391 |
| LMArena Chinese | 1514 | 1463 |
| LMArena French | 1476 | 1429 |
| LMArena German | 1462 | 1395 |
| LMArena Japanese | 1446 | 1324 |
| LMArena Korean | 1420 | 1358 |
| LMArena Russian | 1450 | 1387 |
| LMArena Spanish | 1455 | 1420 |

## Instruction Following

- GPT-5.6 Terra: 76.6 (#38)
- MiMo-V2-Flash: 73.7 (#115)

| Benchmark | GPT-5.6 Terra | MiMo-V2-Flash |
|---|---|---|
| LMArena Instruction Following | 1453 | 1392 |

## Long Context

- GPT-5.6 Terra: 44.4 (#64)
- MiMo-V2-Flash: 43.0 (#106)

| Benchmark | GPT-5.6 Terra | MiMo-V2-Flash |
|---|---|---|
| LMArena Longer Query | 1452 | 1409 |

## Writing & Preference

- GPT-5.6 Terra: 70.4 (#21)
- MiMo-V2-Flash: 59.9 (#101)

| Benchmark | GPT-5.6 Terra | MiMo-V2-Flash |
|---|---|---|
| LMArena Text | 1446 | 1411 |
| LMArena Creative Writing | 1411 | 1375 |
| LMArena Multi-Turn | 1451 | 1404 |
| EQ-Bench Creative Writing | 1855 | — |
| EQ-Bench 4 | 1234 | — |

## FAQ

### Is GPT-5.6 Terra better than MiMo-V2-Flash?

GPT-5.6 Terra is the stronger model overall, scoring 59.1 to 40.8 on the Noometry Index. MiMo-V2-Flash costs 26× less per token, which makes it the better buy when GPT-5.6 Terra's lead doesn't matter for your workload.

### Which is cheaper, GPT-5.6 Terra 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-5.6 Terra lists at $2 and $12.

### Is GPT-5.6 Terra or MiMo-V2-Flash better for coding?

GPT-5.6 Terra scores higher on coding benchmarks: 57.1 versus 35.8 in the Noometry coding category.

### Which has the bigger context window?

GPT-5.6 Terra does, with 1.05M tokens against 262K.

### How many benchmarks do GPT-5.6 Terra and MiMo-V2-Flash share?

21 benchmarks have published results for both models. GPT-5.6 Terra has 52 scored results on Noometry and MiMo-V2-Flash has 21.