Head to head · Open-weight models you run yourself · October 2026 research run
MiMo-V2.6-Flash-RL vs Step 3.7 Flash
MiMo-V2.6-Flash-RL scores 61 (C) on agent readiness against Step 3.7 Flash's 59.8 (C), and leads in 1 of 4 scored categories. Step 3.7 Flash leads on reach. Both do open-weight models you run yourself.
Best open-weight models you download and run yourself for AI agents · All 6359 open weights comparisons
Which one, for what
Best for Teams with a GPU server, or a provider account, that want an open agent model with a very long context
Ahead on
- Documentation and upkeep, 59 against 39
Watch for
178 GB at 4 bits, so it needs about 200 GB of memory
Best for Teams with a GPU server or a provider account that want an open, long-context agent model with vision
Ahead on
- Reach, 70 against 65
Watch for
About 131 GB to run at 4 bits with images, over a 128 GB machine's share
Why the edge
Each category where one leads by five points or more, with the reason behind each side's score from its assessment. The numbers are in the table below; this is what they stand for.
Documentation and upkeep MiMo-V2.6-Flash-RL +20
MiMo-V2.6-Flash-RL 59
Model card 14, Intended use, the architecture, the parameters, the context and the languages (in the metadata) are on the card. Training data 5, A description of the training method with no data sources, sizes or cut-off. Last change 20, the last commits, on 28 October 2026, updated the card, 13 days before this check. Responsiveness 5, Of the 13 most recent discussions that aren't pull requests (21 September to 6 November 2026), 3 have a reply from a XiaomiMiMo member, which is a few. Version policy 5, MiMo-V2.5 stays in its own repositories and V2.6 came out in new ones, with no dated note on the older cards that we read. File health 10, Config, template and card agree on the architecture and the 1M context, and two early faults (invalid JSON in the draft model's config, preprocessor values) were fixed in commits that say so. 14 + 5 + 20 + 5 + 5 + 10 = 59.
Step 3.7 Flash 39
Model card 14, Intended use, the architecture, the parameters, the context and the language (in the metadata) are on the card. Training data 0, Nothing on the card about the training data. Last change 10, the last commit, on 3 June 2026, fixed the modelling code, 160 days before this check and within 180. Responsiveness 0, none of the 11 most recent discussions that aren't pull requests (29 May to 24 June 2026) has a reply from a stepfun-ai member, counted on 10 November by author flags and dates with a script, text not read. Version policy 5, Step-3.5-Flash stays in its own repositories and 3.7 came out in new ones, with no dated note on the older cards that we read. File health 10, Config, template and card agree on the architecture and the context, and June commits fixed the modelling code. 14 + 0 + 10 + 0 + 5 + 10 = 39.
Reach Step 3.7 Flash +5
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.
Step 3.7 Flash 70
Memory 5, the smallest build at 4 bits is StepFun's IQ4_XS GGUF, 104.99 GB with the 3.97 GB projector, and 108.96 GB × 1.2 = 130.8 GB, over what the reference machine can give a model and within 256 GB. The IQ3 and Q3 builds are below 4 bits and aren't read. Runtimes 20, Released vLLM 0.33.0, SGLang 0.5.23 and Transformers 5.22.2 have the step3p7 model, and llama.cpp b12242 has the architecture, with StepFun's own GGUF. Four at 5 each, and the card documents all four. Builds 15, StepFun publishes GGUF at five quantised precisions, an FP8 build and an NVFP4 build. Terms 15, Apache 2.0 in the card's metadata and its licence section, an OSI licence with nothing added. Download 10, the Hub API reports gated false for all four repositories on 10 November 2026, so the files download with no account and nothing to accept. Hosted 5, StepFun's own API serves it, per the card and our StepFun API listing, and Featherless and DeepInfra are live for it on Hugging Face. 5 + 20 + 15 + 15 + 10 + 5 = 70.
Score by category
| Category | Weight this run | MiMo-V2.6-Flash-RL | Step 3.7 Flash | Edge |
|---|---|---|---|---|
| Capability | 35%pending | pending | pending | not scored in this run |
| Reach | 25%25 | 65 | 70 | Step 3.7 Flash +5 |
| Risk | 20%20 | 45 | 45 | even |
| Agent interface | 10%10 | 85 | 85 | even |
| Documentation and upkeep | 10%10 | 59 | 39 | MiMo-V2.6-Flash-RL +20 |
| Negative events | ≤15 | 0 | 0 | |
| Total | C 61/100 | C 59.8/100 |
Facts side by side
| Fact | MiMo-V2.6-Flash-RL | Step 3.7 Flash |
|---|---|---|
| Kind | Open-weight model | Open-weight model |
| Vendor | Xiaomi (MiMo team) | StepFun |
| Hosted endpoint | no (local only) | no (local only) |
| Transports | ||
| Auth | None | None |
| Pricing | Free | Free |
| x402 | no | no |
| Licence | MIT (metadata only, no LICENSE file) | Apache-2.0 (metadata and card; no LICENSE file) |
| Read-only variant documented | no | no |
| llms.txt | no | no |
| Last release | 2026-10-28 | 2026-06-03 |
| Terms last updated | no document linked | no document linked |
| Privacy policy last updated | no document linked | no document linked |
Verdicts
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.
Step 3.7 Flash
A capable open agent model with a clean licence, every kind of build and four released runtimes. Two things hold it back: it's a little too big for a 128 GB machine at 4 bits, whatever the card says, and StepFun has gone quiet on the repository since June. No safety results, limitations or data description.
Before you call either
MiMo-V2.6-Flash-RL
- Plan for a provider unless you have a multi-GPU server: Xiaomi's API platform, OpenRouter or Novita
- On SGLang or vLLM pass
--tool-call-parser mimo --reasoning-parser mimo - Use temperature 1.0 and top_p 0.95, as the card recommends
- 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
- Skip the dflash folder unless you need speculative decoding. Its mask_embedding.pt is a pickle
- The Use Restrictions section asks for human oversight of high-risk actions
Step 3.7 Flash
- On a 128 GB machine the 4-bit GGUF won't fit with a working context. Use StepFun's API or a provider, or a server
- On vLLM or SGLang pass
--tool-call-parser step3p5 --reasoning-parser step3p5 - The card's commands pass trust-remote-code. Released Transformers 5.22.2 has the model built in if you'd rather not run the repository's code
- For llama.cpp load the mmproj file from StepFun's GGUF repository for image input
- StepFun's API has two hosts. Use the one where your key was issued,
api.stepfun.aiorapi.stepfun.com - The same model is on our StepFun API listing, with prices and terms
Questions
Which is better for AI agents, MiMo-V2.6-Flash-RL or Step 3.7 Flash?
MiMo-V2.6-Flash-RL scores 61 (C) on agent readiness against Step 3.7 Flash's 59.8 (C), and leads in 1 of 4 scored categories. Step 3.7 Flash leads on reach.
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Machine-readable
- This page as Markdown
/compare/mimo-v2-6-flash-rl-vs-step-3-7-flash.md· slim.min.md· JSON.json(or sendAccept: text/markdown) - Each listing in full
/api/v1/tools/mimo-v2-6-flash-rl.json·/api/v1/tools/step-3-7-flash.json - From a terminal
anchor compare mimo-v2-6-flash-rl step-3-7-flash(the CLI) - Over MCP
compare_tools {"a": "mimo-v2-6-flash-rl", "b": "step-3-7-flash"}at/mcp, no key