MiMo-V2.6-Flash

MiMo Flash model for multimodal coding agents and long-context automation
- Context
- 1.1M
- Released
- 3w ago
- Parameters
- —
- Input / 1M tokens
- $0.14
- Output / 1M tokens
- $0.28
- Cached input / 1M tokens
- $0.0028
Sources:models.devOpenRouter
Benchmarks
DeepSWE is the primary coding benchmark where an exact model evaluation exists. Other sourced evaluations appear below; missing scores are not zero.
Not evaluated in DeepSWE 1.1 as of 2026-09-22. Results are only shown for exact model versions in the official dataset. Official leaderboard.
No benchmark results have been matched to this model yet.
Specifications
- Developer
- Xiaomi
- Model family
- MiMo
- Type
- Language model
- Predecessor
- —
- Successor
- —
- Released
- September 22, 2026
- Model ID
xiaomi/mimo-v2.6-flash- Openness
- Open weights
- License
- —
- Parameters
- —
- Input modalities
- text, image, video, audio
- Output modalities
- text
- Modality
- text+image+audio+video->text
- Tokenizer
- Other
- Max output tokens
- 131K
- Hugging Face
- XiaomiMiMo/MiMo-V2.6-Flash-RL
- Source freshness
- Metadata synced Oct 8, 2026, 10:17 PM UTC
Additional source evidence
- Source model
- xiaomi/mimo-v2.6-flash
- Source family
- mimo
- Last updated
- 2026-09-22
- Model context
- 1.0M
- Model output limit
- 131K
- Open weights
- Yes
- File attachments
- Yes
- Reasoning
- Yes
- Tool calling
- Yes
- Temperature control
- Yes
Downloadable weights
Published benchmarks
| Benchmark | Score | Evaluation details | Evidence |
|---|---|---|---|
| DeepSWE | 67.9 · score | 1.1 | Source |
| ProgramBench | 26 · score | — | Source |
| MiMo Code Bench | 61.2 · score | — | Source |
| AutomationBench | 52.3 · score | 1.0.6 | Source |
| Toolathlon-Verified | 73.6 · score | — | Source |
| Agents' Last Exam | 27.6 · score | — | Source |
| Terminal-Bench | 28.8 · score | 4.0 | Source |
| Terminal-Bench | 87.6 · score | 2.1 | Source |
| OSWorld-Verified | 80.8 · score | — | Source |
| JobBench | 61.2 · score | — | Source |
| CyberGym | 95.1 · score | — | Source |
| MiMo Cyber Bench | 77.2 · score | — | Source |
| ExploitGym | 6 · score | — | Source |
| ExploitBench | 25.3 · score | — | Source |
| SEC-Bench Pro | 47.5 · score | — | Source |
| MiMo VisualCoding | 71.5 · score | — | Source |
Complete source record (JSON)
{
"id": "xiaomi/mimo-v2.6-flash",
"name": "MiMo-V2.6-Flash",
"description": "MiMo Flash model for multimodal coding agents and long-context automation",
"family": "mimo",
"last_updated": "2026-09-22",
"attachment": true,
"reasoning": true,
"tool_call": true,
"temperature": true,
"modalities": {
"input": [
"text",
"image",
"audio",
"video"
],
"output": [
"text"
]
},
"limit": {
"context": 1048576,
"output": 131072
},
"benchmarks": [
{
"name": "DeepSWE",
"score": 67.9,
"source": "https://huggingface.co/XiaomiMiMo/MiMo-V2.6-Flash-RL",
"metric": "score",
"version": "1.1"
},
{
"name": "ProgramBench",
"score": 26,
"source": "https://huggingface.co/XiaomiMiMo/MiMo-V2.6-Flash-RL",
"metric": "score"
},
{
"name": "MiMo Code Bench",
"score": 61.2,
"source": "https://huggingface.co/XiaomiMiMo/MiMo-V2.6-Flash-RL",
"metric": "score"
},
{
"name": "AutomationBench",
"score": 52.3,
"source": "https://huggingface.co/XiaomiMiMo/MiMo-V2.6-Flash-RL",
"metric": "score",
"version": "1.0.6"
},
{
"name": "Toolathlon-Verified",
"score": 73.6,
"source": "https://huggingface.co/XiaomiMiMo/MiMo-V2.6-Flash-RL",
"metric": "score"
},
{
"name": "Agents' Last Exam",
"score": 27.6,
"source": "https://huggingface.co/XiaomiMiMo/MiMo-V2.6-Flash-RL",
"metric": "score"
},
{
"name": "Terminal-Bench",
"score": 28.8,
"source": "https://huggingface.co/XiaomiMiMo/MiMo-V2.6-Flash-RL",
"metric": "score",
"version": "4.0"
},
{
"name": "Terminal-Bench",
"score": 87.6,
"source": "https://huggingface.co/XiaomiMiMo/MiMo-V2.6-Flash-RL",
"metric": "score",
"version": "2.1"
},
{
"name": "OSWorld-Verified",
"score": 80.8,
"source": "https://huggingface.co/XiaomiMiMo/MiMo-V2.6-Flash-RL",
"metric": "score"
},
{
"name": "JobBench",
"score": 61.2,
"source": "https://huggingface.co/XiaomiMiMo/MiMo-V2.6-Flash-RL",
"metric": "score"
},
{
"name": "CyberGym",
"score": 95.1,
"source": "https://huggingface.co/XiaomiMiMo/MiMo-V2.6-Flash-RL",
"metric": "score"
},
{
"name": "MiMo Cyber Bench",
"score": 77.2,
"source": "https://huggingface.co/XiaomiMiMo/MiMo-V2.6-Flash-RL",
"metric": "score"
},
{
"name": "ExploitGym",
"score": 6,
"source": "https://huggingface.co/XiaomiMiMo/MiMo-V2.6-Flash-RL",
"metric": "score"
},
{
"name": "ExploitBench",
"score": 25.3,
"source": "https://huggingface.co/XiaomiMiMo/MiMo-V2.6-Flash-RL",
"metric": "score"
},
{
"name": "SEC-Bench Pro",
"score": 47.5,
"source": "https://huggingface.co/XiaomiMiMo/MiMo-V2.6-Flash-RL",
"metric": "score"
},
{
"name": "MiMo VisualCoding",
"score": 71.5,
"source": "https://huggingface.co/XiaomiMiMo/MiMo-V2.6-Flash-RL",
"metric": "score"
}
],
"release_date": "2026-09-22",
"open_weights": true,
"weights": [
{
"label": "Hugging Face",
"url": "https://huggingface.co/XiaomiMiMo/MiMo-V2.6-Flash-RL"
}
]
}Infrastructure
Provider availability
| Provider | Endpoint | Context | Input /M tokens | Output /M tokens | Cached input /M tokens | Cache write /M tokens | Uptime 1d | Data handling |
|---|---|---|---|---|---|---|---|---|
| darkbloom/fp4 | 1.0M | $0.10 | $0.28 | $0.05 | — | 95.74% | ZDR: NoTraining: Unknown Prompt logging: Unknown Retention: Unknown Checked 2026-10-15 | |
| makora/fp8 | 1.0M | $0.13 | $0.28 | $0.002 | — | 94.72% | ZDR: Yes | |
| deepinfra/fp8 | 1.0M | $0.13 | $0.27 | $0.00266 | — | 88.53% | ZDR: YesTraining: Unknown Prompt logging: Unknown Retention: Unknown Checked 2026-10-15 | |
| gmicloud/bf16 | 1.1M | $0.14 | $0.28 | $0.003 | — | 45.80% | ZDR: NoTraining: Unknown Prompt logging: Unknown Retention: Unknown Checked 2026-10-15 | |
| novita/fp8 | 1.0M | $0.14 | $0.28 | $0.0028 | — | 98.89% | ZDR: YesTraining: Unknown Prompt logging: Unknown Retention: Unknown Checked 2026-10-15 | |
| xiaomi/fp8 | 1.0M | $0.14 | $0.28 | $0.0028 | — | 99.58% | ZDR: NoTraining: Unknown Prompt logging: Unknown Retention: Unknown Checked 2026-10-15 | |
| io-net/fp8 | 1.0M | $0.15 | $0.29 | $0.02 | — | 98.74% | ZDR: YesTraining: Unknown Prompt logging: Unknown Retention: Unknown Checked 2026-10-15 | |
| venice/fp8 | 1M | $0.18 | $0.35 | $0.00375 | — | 56.13% | ZDR: YesTraining: Unknown Prompt logging: Unknown Retention: Unknown Checked 2026-10-15 |
Provider data:OpenRouter
Deployment graph
Can I run this?
Vertical Tabs only shows compatibility when it has structured evidence tying this exact model to hardware, runtime, quantization, memory use, and observed performance.