# Cola2 vs MiMo-V2.6-Flash-RL

> MiMo-V2.6-Flash-RL scores 61 (C) to Cola2's 33.9 (F) for open-weight models you run yourself. Prices, MCP, x402, uptime and agent notes side by side.

- Canonical: https://www.anchorterminal.com/compare/cola2-vs-mimo-v2-6-flash-rl
- Markdown: https://www.anchorterminal.com/compare/cola2-vs-mimo-v2-6-flash-rl.md (~8,750 tokens)
- Site index for agents: https://www.anchorterminal.com/llms.txt (the key docs and every listing in one file, at most 16 MB, about 4 million tokens: https://www.anchorterminal.com/llms-full.txt)
- API: https://www.anchorterminal.com/api/v1/index.json
- MCP: https://www.anchorterminal.com/mcp (the whole catalogue as tools, no key)
- DNS: dig +short TXT <slug>.grade.anchorterminal.com (the grade as a DNS TXT record, for a sandbox with no HTTP where names still resolve; also top., best.<category>. and <a>.vs.<b>. under the zone, and the same under grade.letme.dev)
- Licence: CC BY 4.0, credit Anchor Terminal and link this page (https://www.anchorterminal.com/terms/#data)
- Updated: 2026-11-10

MiMo-V2.6-Flash-RL scores 61 (C) on agent readiness against Cola2's 33.9 (F), and leads in every scored category. Both do open-weight models you run yourself.

- Cola2: grade F, 33.9/100, rank #160 of 160 open-weight models. Markdown https://www.anchorterminal.com/tools/cola2.md · JSON https://www.anchorterminal.com/api/v1/tools/cola2.json
- MiMo-V2.6-Flash-RL: grade C, 61/100, rank #75 of 160 open-weight models. Markdown https://www.anchorterminal.com/tools/mimo-v2-6-flash-rl.md · JSON https://www.anchorterminal.com/api/v1/tools/mimo-v2-6-flash-rl.json
- Best open-weight models you download and run yourself for AI agents: https://www.anchorterminal.com/best/open-weights/index.md
- All 6359 open weights comparisons: https://www.anchorterminal.com/compare/open-weights/index.md

## Which one, for what

### Cola2 (F)

Good for: Researchers working on latent or diffusion language models who want a checkpoint to study

Watch for: No licence stated for the weights

### MiMo-V2.6-Flash-RL (C)

Good for: Teams with a GPU server, or a provider account, that want an open agent model with a very long context

Ahead on:
- Reach, 65 against 25
- Risk, 45 against 40
- Agent interface, 85 against 20

Watch for: 178 GB at 4 bits, so it needs about 200 GB of memory


## Why the edge

### Agent interface: MiMo-V2.6-Flash-RL +65

- Cola2 (20): Chat template 20, A chat template in tokenizer_config.json (4,116 characters), which came with the Qwen3 tokenizer. Tool-calling format 0, none. Trained tool calling 0, not trained for tool calling. Structured output 0, Nothing about JSON or schema-constrained output. Reasoning control 0, no reasoning mode. Context 0, no context length is stated. 20 + 0 + 0 + 0 + 0 + 0 = 20.
- MiMo-V2.6-Flash-RL (85): Chat template 20, chat_template.jinja in the repository (3,868 characters), with a copy in tokenizer_config.json. Tool-calling format 25, the card names the parser to use in two runtimes: the mimo tool-call parser in SGLang and in vLLM, with auto tool choice, and both ship it in a release. Trained tool calling 20, the card describes reinforcement learning on coding and general agent tasks across several harnesses, and the template renders every call in a turn. Structured output 0, Nothing on the card about JSON or schema-constrained output. Reasoning control 10, the template has an enable_thinking switch and keeps reasoning_content, and the card names the mimo reasoning parser for SGLang and vLLM, which returns the reasoning apart from the answer. Context 10, 1M tokens per the card's model summary, and 1,048,576 positions in config.json. 20 + 25 + 20 + 0 + 10 + 10 = 85.

### Reach: MiMo-V2.6-Flash-RL +40

- Cola2 (25): Memory 15, the only build is the F32 safetensors set, 35.07 GB, and 35.07 GB × 1.2 = 42.1 GB, within 64 GB. Loaded as BF16, as the card's example does, it needs about half, but the line reads the file size. Runtimes 0, none of the six runs it in a released version. Builds 0, one set of weights and no quantised build. Terms 0, no licence for the weights. Download 10, the Hub API reports gated false on 10 November 2026, so the files download with no account and nothing to accept. Hosted 0, Hugging Face maps no inference provider to it, and nothing names an API that serves it. 15 + 0 + 0 + 0 + 10 + 0 = 25.
- MiMo-V2.6-Flash-RL (65): Memory 5, the smallest build at 4 bits or better is ggml-org's MXFP4 GGUF, 168.93 GB with its projector, and 168.93 GB × 1.2 = 202.7 GB, within 256 GB. Xiaomi's own files are 177.74 GB. ggml-org's Q2_K is below 4 bits and isn't read. Runtimes 20, Released vLLM 0.33.0 and SGLang 0.5.23 have the mimo_v2 model and the mimo parsers, Transformers 5.22.2 has a mimo_v2_flash model, and llama.cpp b12242 has the architecture, with a GGUF from its own organisation. Builds 10, one precision from Xiaomi, the 4-bit files it releases. Terms 15, MIT in the card's metadata, an OSI licence. Download 10, the Hub API reports gated false on 10 November 2026, so the files download with no account and nothing to accept. Hosted 5, the card says it is on Xiaomi's MiMo Open Platform API and on OpenRouter, and Novita is live for it on Hugging Face. 5 + 20 + 10 + 15 + 10 + 5 = 65.

### Risk: MiMo-V2.6-Flash-RL +5

- Cola2 (40): File safety 15, safetensors only, no .bin, .pt or .pth files (25). Provenance 15, the files sit in the ByteDance-Seed organisation, which the ByteDance-Seed GitHub repository for the model links to (10). Safety evaluation 0, no safety results. Agent guidance 5, General cautions in the GitHub model card: not instruction-tuned or safety-aligned, not for use as an assistant, for facts or advice, or for high-impact decisions about people. Licence risk 0, With no licence for the weights there is nothing to hold ByteDance to. Security programme 5, the GitHub repository's SECURITY.md sends reports to ByteDance's security centre and says how they're assessed (5). 15 + 15 + 0 + 5 + 0 + 5 = 40.
- MiMo-V2.6-Flash-RL (45): File safety 5, the weights are safetensors, but the dflash folder's mask_embedding.pt is a pickle beside them (15). Provenance 15, the files sit in the XiaomiMiMo organisation, which mimo.xiaomi.com links to per the Distill listing (10). Safety evaluation 0, no safety results on the card. Agent guidance 5, General cautions only. Licence risk 15, MIT has no use policy, threshold or change clause. Security programme 5, Xiaomi runs a company security centre for reporting flaws, as read for the Distill listing (5). 5 + 15 + 0 + 5 + 15 + 5 = 45.

## Score by category

| Category | Weight | Cola2 | MiMo-V2.6-Flash-RL | Edge |
| --- | --- | --- | --- | --- |
| Capability | 35%, pending | pending | pending | not scored in this run |
| Reach | 25% (25 this run) | 25 | 65 | MiMo-V2.6-Flash-RL +40 |
| Risk | 20% (20 this run) | 40 | 45 | MiMo-V2.6-Flash-RL +5 |
| Agent interface | 10% (10 this run) | 20 | 85 | MiMo-V2.6-Flash-RL +65 |
| Documentation and upkeep | 10% (10 this run) | 58 | 59 | MiMo-V2.6-Flash-RL +1 |
| Negative events | ≤15 | 0 | 0 | |
| **Total** | | **33.9 · F** | **61 · C** | |

## Facts side by side

| Fact | Cola2 | MiMo-V2.6-Flash-RL |
| --- | --- | --- |
| Kind | Open-weight model | Open-weight model |
| Vendor | ByteDance (Seed) | Xiaomi (MiMo team) |
| Hosted endpoint | no (local only) | no (local only) |
| Transports |  |  |
| Auth | None | None |
| Pricing | Free | Free |
| x402 | no | no |
| Licence | None stated for the weights (the code is Apache 2.0) | MIT (metadata only, no LICENSE file) |
| Read-only variant documented | no | no |
| llms.txt | no | no |
| Last release | 2026-11-06 | 2026-10-28 |
| Terms last updated | no document linked | no document linked |
| Privacy policy last updated | no document linked | no document linked |

## Verdicts

**Cola2.** A research release, and an honest one: ByteDance Seed says it's a base model with an unconverged latent stage, scoring below Llama-3-8B on its own table. It's here for people studying continuous-latent generation. Agents can't use it as a model: 32-token completions, no chat or tools, the repository's own code to load it, and no licence on the weights.

**MiMo-V2.6-Flash-RL.** A large agent model with an open licence: text, images, video and audio, a 1M context, tool calling it was trained for, and code in four released runtimes. It's a server model, 178 GB at 4 bits, and the card's commands run the repository's code. No safety results, little said about data, and few questions answered.

## Before you call either

### Cola2

1. Don't plan to use this as your model. It completes short prompts and wasn't tuned to follow instructions
2. Don't use it commercially on the strength of this listing. The weights have no stated licence
3. If you study it, read modeling_cola2.py first: trust_remote_code runs it
4. Pin Transformers below 5, as the card requires
5. Pass a seeded torch.Generator to generate(). Output varies between runs even with greedy decoding
6. Check the download with `sha256sum -c SHA256SUMS`

### MiMo-V2.6-Flash-RL

1. Plan for a provider unless you have a multi-GPU server: Xiaomi's API platform, OpenRouter or Novita
2. On SGLang or vLLM pass `--tool-call-parser mimo --reasoning-parser mimo`
3. Use temperature 1.0 and top_p 0.95, as the card recommends
4. The card's commands pass trust-remote-code. Read the repository's three Python files first, or use Transformers 5.22.2, which has the model built in
5. Skip the dflash folder unless you need speculative decoding. Its mask_embedding.pt is a pickle
6. The Use Restrictions section asks for human oversight of high-risk actions

## Questions

### Which is better for AI agents, Cola2 or MiMo-V2.6-Flash-RL?

MiMo-V2.6-Flash-RL scores 61 (C) on agent readiness against Cola2's 33.9 (F), and leads in every scored category.


## For agents

- This comparison as JSON: https://www.anchorterminal.com/compare/cola2-vs-mimo-v2-6-flash-rl.json, and with the fewest tokens: https://www.anchorterminal.com/compare/cola2-vs-mimo-v2-6-flash-rl.min.md
- Over MCP at https://www.anchorterminal.com/mcp (no key): `compare_tools {"a": "cola2", "b": "mimo-v2-6-flash-rl"}`. From a terminal: `anchor compare cola2 mimo-v2-6-flash-rl`
- Each listing in full: https://www.anchorterminal.com/api/v1/tools/cola2.json and https://www.anchorterminal.com/api/v1/tools/mimo-v2-6-flash-rl.json

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- [MiMo-V2.6-Flash-RL vs WeVisOne-VL-2B](https://www.anchorterminal.com/compare/mimo-v2-6-flash-rl-vs-wevisone-vl-2b.md)
- [MiMo-V2.6-Flash-RL vs WeVisOne-VL-4B](https://www.anchorterminal.com/compare/mimo-v2-6-flash-rl-vs-wevisone-vl-4b.md)
- [MiMo-V2.6-Flash-RL vs ZAYA1-8B](https://www.anchorterminal.com/compare/mimo-v2-6-flash-rl-vs-zaya1-8b.md)

---

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