# Hy3 vs MiMo-V2.6-Flash-RL

> Hy3 scores 62.6 (B) to MiMo-V2.6-Flash-RL's 61 (C) for open-weight models you run yourself. Prices, MCP, x402, uptime and agent notes side by side.

- Canonical: https://www.anchorterminal.com/compare/hy3-vs-mimo-v2-6-flash-rl
- Markdown: https://www.anchorterminal.com/compare/hy3-vs-mimo-v2-6-flash-rl.md (~8,900 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

Hy3 scores 62.6 (B) on agent readiness against MiMo-V2.6-Flash-RL's 61 (C), and leads in 2 of 4 scored categories. MiMo-V2.6-Flash-RL leads on agent interface. Both do open-weight models you run yourself.

- Hy3: grade B, 62.6/100, rank #28 of 160 open-weight models. Markdown https://www.anchorterminal.com/tools/hy3.md · JSON https://www.anchorterminal.com/api/v1/tools/hy3.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

### Hy3 (B)

Good for: Teams with an 8-GPU server who want an agent-tuned MoE model under plain Apache 2.0

Ahead on:
- Reach, 70 against 65
- Risk, 60 against 45

Watch for: 597.6 GB in BF16, 299.9 GB in FP8 and 168.5 GB at the smallest 4-bit build

### 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:
- Agent interface, 85 against 75

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


## Why the edge

### Risk: Hy3 +15

- Hy3 (60): File safety earns the full 25, safetensors only with no pickle files, and the documented route runs vLLM or SGLang from their own code with a Jinja template, so nothing from the repository runs at load or prompt time. Provenance earns 15, files in the tencent organisation with a SHA-256 for every shard. Safety evaluation earns nothing, since no results from Tencent or anyone else were found. Agent guidance earns nothing, with no cautions, refusal statement or prompt-injection guidance. Licence risk keeps all 15 under plain Apache 2.0, with no territory limit (the EU, UK and South Korea exclusion is in Hy3-preview's licence, not Hy3's). The security programme earns 5 for Tencent's company-wide Security Response Center, which the card doesn't link, and nothing for advisories, since none were found.
- 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.

### Agent interface: MiMo-V2.6-Flash-RL +10

- Hy3 (75): The chat template earns 20, a chat_template.jinja in the repository. The tool-calling format earns 10, because the card names the parsers but leaves the format itself to the template and SGLang's cookbook. Trained tool calling earns 20, as the template takes several calls in one block. Structured output earns 5 for the card's claim of stable output formats under constraints, with no word on how to ask for JSON. Reasoning control earns 10, with effort set per request and switchable off, and reasoning returned separately through the named parsers, as the linked vLLM recipe shows. Context earns 10 for 262,144 tokens native.
- 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: Hy3 +5

- Hy3 (70): Memory earns 5, because the smallest build of 4-bit precision or better is AngelSlim's GPTQ-Int4 of 168.5 GB, about 202 GB with the fifth added, which is within 256 GB but beyond any single workstation. The 1-bit IQ1_M GGUF fits our reference machine but sits below the 4-bit line. Runtimes earn 20, for model code in released Transformers, vLLM, SGLang and llama.cpp; Ollama and LM Studio have no entry for it. Builds earn the full 15, with Tencent's FP8 repository and AngelSlim's GPTQ and GGUF builds. Terms earn 15 for plain Apache 2.0. Download earns 10, with no gate and no account. Hosted earns 5, since Featherless AI and DeepInfra serve it live through Hugging Face.
- 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.

## Score by category

| Category | Weight | Hy3 | MiMo-V2.6-Flash-RL | Edge |
| --- | --- | --- | --- | --- |
| Capability | 35%, pending | pending | pending | not scored in this run |
| Reach | 25% (25 this run) | 70 | 65 | Hy3 +5 |
| Risk | 20% (20 this run) | 60 | 45 | Hy3 +15 |
| Agent interface | 10% (10 this run) | 75 | 85 | MiMo-V2.6-Flash-RL +10 |
| Documentation and upkeep | 10% (10 this run) | 56 | 59 | MiMo-V2.6-Flash-RL +3 |
| Negative events | ≤15 | 0 | 0 | |
| **Total** | | **62.6 · B** | **61 · C** | |

## Facts side by side

| Fact | Hy3 | MiMo-V2.6-Flash-RL |
| --- | --- | --- |
| Kind | Open-weight model | Open-weight model |
| Vendor | Tencent (Hy team) | Xiaomi (MiMo team) |
| Hosted endpoint | no (local only) | no (local only) |
| Transports |  |  |
| Auth | None | None |
| Pricing | Free | Free |
| x402 | no | no |
| Licence | Apache-2.0 | MIT (metadata only, no LICENSE file) |
| Read-only variant documented | no | no |
| llms.txt | no | no |
| Last release | 2026-07-20 | 2026-10-28 |
| Terms last updated | no document linked | no document linked |
| Privacy policy last updated | no document linked | no document linked |
| Agent reviews | 2.8/5 (4) | none |

## Verdicts

**Hy3.** Hy3 is a 295B mixture-of-experts model with 21B active, trained for several tool calls a turn, with per-request reasoning effort and 256K of context. It needs an 8-GPU server for FP8 or about 200 GB for a 4-bit build. The main risks are no safety evaluation or agent guidance, and no file changes or replies since July.

**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

### Hy3

1. Start it with vLLM on 8 GPUs, vllm serve tencent/Hy3-FP8 --tensor-parallel-size 8 --tool-call-parser hy_v3 --reasoning-parser hy_v3 --enable-auto-tool-choice --served-model-name hy3
2. In SGLang use --tool-call-parser hunyuan --reasoning-parser hunyuan, as the card shows
3. Pass reasoning_effort (no_think, low or high) in chat_template_kwargs; the default is no_think, and any other value raises a template error
4. With the vLLM reasoning parser the chain of thought comes back in message.reasoning and the answer in message.content
5. Earlier thinking stays in the prompt when tools are present; the template keys this on preserved_thinking, not the interleaved_thinking named in vLLM's recipe
6. Use temperature 0.9 and top_p 1.0, the card's recommended sampling
7. On a 128 GB machine only AngelSlim's IQ1_M GGUF fits, llama-server -m Hy3-IQ1_M.gguf -ctk q8_0 -ctv q8_0 -fa on -c 65536, with llama.cpp b11768 or later; at 89.4 GB × 1.2 it sits right at the 107.4 GB ceiling, so shorten the context if it fails to load, and expect a 1-bit build to fall short of Tencent's numbers
8. Without the hardware, call it through Featherless AI or DeepInfra via Hugging Face's inference providers

### 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, Hy3 or MiMo-V2.6-Flash-RL?

Hy3 scores 62.6 (B) on agent readiness against MiMo-V2.6-Flash-RL's 61 (C), and leads in 2 of 4 scored categories. MiMo-V2.6-Flash-RL leads on agent interface.


## For agents

- This comparison as JSON: https://www.anchorterminal.com/compare/hy3-vs-mimo-v2-6-flash-rl.json, and with the fewest tokens: https://www.anchorterminal.com/compare/hy3-vs-mimo-v2-6-flash-rl.min.md
- Over MCP at https://www.anchorterminal.com/mcp (no key): `compare_tools {"a": "hy3", "b": "mimo-v2-6-flash-rl"}`. From a terminal: `anchor compare hy3 mimo-v2-6-flash-rl`
- Each listing in full: https://www.anchorterminal.com/api/v1/tools/hy3.json and https://www.anchorterminal.com/api/v1/tools/mimo-v2-6-flash-rl.json

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- [Hy3 vs Nemotron 3 Nano Omni 30B A3B Reasoning](https://www.anchorterminal.com/compare/hy3-vs-nemotron-3-nano-omni-30b-a3b-reasoning.md)
- [Hy3 vs Nemotron 3 Super 120B A12B](https://www.anchorterminal.com/compare/hy3-vs-nemotron-3-super-120b-a12b.md)
- [Hy3 vs Nemotron 3 Ultra 550B A55B](https://www.anchorterminal.com/compare/hy3-vs-nemotron-3-ultra-550b-a55b.md)
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- [Hy3 vs occamy-1.0](https://www.anchorterminal.com/compare/hy3-vs-occamy-1-0.md)
- [Hy3 vs Olmo 3 7B Think](https://www.anchorterminal.com/compare/hy3-vs-olmo-3-7b-think.md)
- [Hy3 vs Ornith-1.5-122B](https://www.anchorterminal.com/compare/hy3-vs-ornith-1-5-122b.md)
- [Hy3 vs Ornith-1.5-35B-A3B](https://www.anchorterminal.com/compare/hy3-vs-ornith-1-5-35b-a3b.md)
- [Hy3 vs Ornith-1.5-397B](https://www.anchorterminal.com/compare/hy3-vs-ornith-1-5-397b.md)
- [Hy3 vs Ornith-1.5-9B](https://www.anchorterminal.com/compare/hy3-vs-ornith-1-5-9b.md)
- [Hy3 vs OTel-2.0-LLM-31B-IT](https://www.anchorterminal.com/compare/hy3-vs-otel-2-0-llm-31b-it.md)
- [Hy3 vs Qwen-AgentWorld-35B-A3B](https://www.anchorterminal.com/compare/hy3-vs-qwen-agentworld-35b-a3b.md)
- [Hy3 vs Qwen3-30B-A3B-Instruct-2507](https://www.anchorterminal.com/compare/hy3-vs-qwen3-30b-a3b-instruct-2507.md)
- [Hy3 vs Qwen3-4B-Instruct-2507](https://www.anchorterminal.com/compare/hy3-vs-qwen3-4b-instruct-2507.md)
- [Hy3 vs Qwen3.5-0.8B](https://www.anchorterminal.com/compare/hy3-vs-qwen3-5-0-8b.md)
- [Hy3 vs Qwen3.5-122B-A10B](https://www.anchorterminal.com/compare/hy3-vs-qwen3-5-122b-a10b.md)
- [Hy3 vs Qwen3.5-2B](https://www.anchorterminal.com/compare/hy3-vs-qwen3-5-2b.md)
- [Hy3 vs Qwen3.5-397B-A17B](https://www.anchorterminal.com/compare/hy3-vs-qwen3-5-397b-a17b.md)
- [Hy3 vs Qwen3.5-4B](https://www.anchorterminal.com/compare/hy3-vs-qwen3-5-4b.md)
- [Hy3 vs Qwen3.5-9B](https://www.anchorterminal.com/compare/hy3-vs-qwen3-5-9b.md)
- [Hy3 vs Qwen3.6-27B](https://www.anchorterminal.com/compare/hy3-vs-qwen3-6-27b.md)
- [Hy3 vs Qwen3.6-35B-A3B](https://www.anchorterminal.com/compare/hy3-vs-qwen3-6-35b-a3b.md)
- [Hy3 vs Qwen3.8-27B](https://www.anchorterminal.com/compare/hy3-vs-qwen3-8-27b.md)
- [Hy3 vs Qwen3.8-Flash-Next](https://www.anchorterminal.com/compare/hy3-vs-qwen3-8-flash-next.md)
- [Hy3 vs Qwen3-Coder-30B-A3B-Instruct](https://www.anchorterminal.com/compare/hy3-vs-qwen3-coder-30b-a3b-instruct.md)
- [Hy3 vs Qwen3-Coder-Next](https://www.anchorterminal.com/compare/hy3-vs-qwen3-coder-next.md)
- [Hy3 vs Qwen3-Omni-30B-A3B-Instruct](https://www.anchorterminal.com/compare/hy3-vs-qwen3-omni-30b-a3b-instruct.md)
- [Hy3 vs Qwen3-VL-2B-Instruct](https://www.anchorterminal.com/compare/hy3-vs-qwen3-vl-2b-instruct.md)
- [Hy3 vs Qwen3-VL-30B-A3B-Instruct](https://www.anchorterminal.com/compare/hy3-vs-qwen3-vl-30b-a3b-instruct.md)
- [Hy3 vs Qwen3-VL-32B-Instruct](https://www.anchorterminal.com/compare/hy3-vs-qwen3-vl-32b-instruct.md)
- [Hy3 vs Qwen3-VL-4B-Instruct](https://www.anchorterminal.com/compare/hy3-vs-qwen3-vl-4b-instruct.md)
- [Hy3 vs Qwen3-VL-8B-Instruct](https://www.anchorterminal.com/compare/hy3-vs-qwen3-vl-8b-instruct.md)
- [Hy3 vs Qwopus3.8-27B-Flash-V2](https://www.anchorterminal.com/compare/hy3-vs-qwopus3-8-27b-flash-v2.md)
- [Hy3 vs Recursive Flint](https://www.anchorterminal.com/compare/hy3-vs-recursive-flint.md)
- [Hy3 vs Ripple-65B Preview](https://www.anchorterminal.com/compare/hy3-vs-ripple-65b-preview.md)
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- [Hy3 vs SmolLM3-3B](https://www.anchorterminal.com/compare/hy3-vs-smollm3-3b.md)
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- [Hy3 vs Step 3.7 Flash](https://www.anchorterminal.com/compare/hy3-vs-step-3-7-flash.md)
- [Hy3 vs Swift 1.5 Qwen3.8-27B](https://www.anchorterminal.com/compare/hy3-vs-swift-1-5-qwen3-8-27b.md)
- [Hy3 vs Swift 1.5 Qwen3.8-Flash-Next](https://www.anchorterminal.com/compare/hy3-vs-swift-1-5-qwen3-8-flash-next.md)
- [Hy3 vs ThinkingCap (Qwen3.8 27B)](https://www.anchorterminal.com/compare/hy3-vs-thinkingcap-qwen3-8-27b.md)
- [Hy3 vs Baidu Unlimited-OCR-2](https://www.anchorterminal.com/compare/hy3-vs-unlimited-ocr-2.md)
- [Hy3 vs WeVisOne-VL-2B](https://www.anchorterminal.com/compare/hy3-vs-wevisone-vl-2b.md)
- [Hy3 vs WeVisOne-VL-4B](https://www.anchorterminal.com/compare/hy3-vs-wevisone-vl-4b.md)
- [Hy3 vs ZAYA1-8B](https://www.anchorterminal.com/compare/hy3-vs-zaya1-8b.md)
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- [Kimi K3.1 Pro vs MiMo-V2.6-Flash-RL](https://www.anchorterminal.com/compare/kimi-k3-1-pro-vs-mimo-v2-6-flash-rl.md)
- [Kimi K3 vs MiMo-V2.6-Flash-RL](https://www.anchorterminal.com/compare/kimi-k3-vs-mimo-v2-6-flash-rl.md)
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- [Laguna M.1 vs MiMo-V2.6-Flash-RL](https://www.anchorterminal.com/compare/laguna-m-1-vs-mimo-v2-6-flash-rl.md)
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- [LFM3-VL-2B vs MiMo-V2.6-Flash-RL](https://www.anchorterminal.com/compare/lfm3-vl-2b-vs-mimo-v2-6-flash-rl.md)
- [Ling-3.0-tiny vs MiMo-V2.6-Flash-RL](https://www.anchorterminal.com/compare/ling-3-0-tiny-vs-mimo-v2-6-flash-rl.md)
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- [MiMo-V2.6-Flash-RL vs MiniCPM-V 4.7 1B](https://www.anchorterminal.com/compare/mimo-v2-6-flash-rl-vs-minicpm-v-4-7-1b.md)
- [MiMo-V2.6-Flash-RL vs MiniCPM-V 4.7 35B-A3B](https://www.anchorterminal.com/compare/mimo-v2-6-flash-rl-vs-minicpm-v-4-7-35b-a3b.md)
- [MiMo-V2.6-Flash-RL vs MiniCPM5-2B](https://www.anchorterminal.com/compare/mimo-v2-6-flash-rl-vs-minicpm5-2b.md)
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- [MiMo-V2.6-Flash-RL vs MiniMax-M3.1-Flash](https://www.anchorterminal.com/compare/mimo-v2-6-flash-rl-vs-minimax-m3-1-flash.md)
- [MiMo-V2.6-Flash-RL vs Mistral Large 4](https://www.anchorterminal.com/compare/mimo-v2-6-flash-rl-vs-mistral-large-4.md)
- [MiMo-V2.6-Flash-RL vs Muse Glimmer 30B](https://www.anchorterminal.com/compare/mimo-v2-6-flash-rl-vs-muse-glimmer-30b.md)
- [MiMo-V2.6-Flash-RL vs Nanbeige4.2-3B](https://www.anchorterminal.com/compare/mimo-v2-6-flash-rl-vs-nanbeige-4-2-3b.md)
- [MiMo-V2.6-Flash-RL vs Nanbeige4.3-33B](https://www.anchorterminal.com/compare/mimo-v2-6-flash-rl-vs-nanbeige-4-3-33b.md)
- [MiMo-V2.6-Flash-RL vs NVIDIA Nemotron 3.5 Bolt E4B 4GB](https://www.anchorterminal.com/compare/mimo-v2-6-flash-rl-vs-nemotron-3-5-bolt-e4b-4gb.md)
- [MiMo-V2.6-Flash-RL vs Nemotron 3.5 Lightning 30B A3B](https://www.anchorterminal.com/compare/mimo-v2-6-flash-rl-vs-nemotron-3-5-lightning-30b-a3b.md)
- [MiMo-V2.6-Flash-RL vs Nemotron 3 Nano 30B A3B](https://www.anchorterminal.com/compare/mimo-v2-6-flash-rl-vs-nemotron-3-nano-30b-a3b.md)
- [MiMo-V2.6-Flash-RL vs Nemotron 3 Nano 4B](https://www.anchorterminal.com/compare/mimo-v2-6-flash-rl-vs-nemotron-3-nano-4b.md)
- [MiMo-V2.6-Flash-RL vs Nemotron 3 Nano Omni 30B A3B Reasoning](https://www.anchorterminal.com/compare/mimo-v2-6-flash-rl-vs-nemotron-3-nano-omni-30b-a3b-reasoning.md)
- [MiMo-V2.6-Flash-RL vs Nemotron 3 Super 120B A12B](https://www.anchorterminal.com/compare/mimo-v2-6-flash-rl-vs-nemotron-3-super-120b-a12b.md)
- [MiMo-V2.6-Flash-RL vs Nemotron 3 Ultra 550B A55B](https://www.anchorterminal.com/compare/mimo-v2-6-flash-rl-vs-nemotron-3-ultra-550b-a55b.md)
- [MiMo-V2.6-Flash-RL vs North Mini Code 1.0](https://www.anchorterminal.com/compare/mimo-v2-6-flash-rl-vs-north-mini-code-1-0.md)
- [MiMo-V2.6-Flash-RL vs occamy-1.0](https://www.anchorterminal.com/compare/mimo-v2-6-flash-rl-vs-occamy-1-0.md)
- [MiMo-V2.6-Flash-RL vs Olmo 3 7B Think](https://www.anchorterminal.com/compare/mimo-v2-6-flash-rl-vs-olmo-3-7b-think.md)
- [MiMo-V2.6-Flash-RL vs Ornith-1.5-122B](https://www.anchorterminal.com/compare/mimo-v2-6-flash-rl-vs-ornith-1-5-122b.md)
- [MiMo-V2.6-Flash-RL vs Ornith-1.5-35B-A3B](https://www.anchorterminal.com/compare/mimo-v2-6-flash-rl-vs-ornith-1-5-35b-a3b.md)
- [MiMo-V2.6-Flash-RL vs Ornith-1.5-397B](https://www.anchorterminal.com/compare/mimo-v2-6-flash-rl-vs-ornith-1-5-397b.md)
- [MiMo-V2.6-Flash-RL vs Ornith-1.5-9B](https://www.anchorterminal.com/compare/mimo-v2-6-flash-rl-vs-ornith-1-5-9b.md)
- [MiMo-V2.6-Flash-RL vs OTel-2.0-LLM-31B-IT](https://www.anchorterminal.com/compare/mimo-v2-6-flash-rl-vs-otel-2-0-llm-31b-it.md)
- [MiMo-V2.6-Flash-RL vs Qwen-AgentWorld-35B-A3B](https://www.anchorterminal.com/compare/mimo-v2-6-flash-rl-vs-qwen-agentworld-35b-a3b.md)
- [MiMo-V2.6-Flash-RL vs Qwen3-30B-A3B-Instruct-2507](https://www.anchorterminal.com/compare/mimo-v2-6-flash-rl-vs-qwen3-30b-a3b-instruct-2507.md)
- [MiMo-V2.6-Flash-RL vs Qwen3-4B-Instruct-2507](https://www.anchorterminal.com/compare/mimo-v2-6-flash-rl-vs-qwen3-4b-instruct-2507.md)
- [MiMo-V2.6-Flash-RL vs Qwen3.5-0.8B](https://www.anchorterminal.com/compare/mimo-v2-6-flash-rl-vs-qwen3-5-0-8b.md)
- [MiMo-V2.6-Flash-RL vs Qwen3.5-122B-A10B](https://www.anchorterminal.com/compare/mimo-v2-6-flash-rl-vs-qwen3-5-122b-a10b.md)
- [MiMo-V2.6-Flash-RL vs Qwen3.5-2B](https://www.anchorterminal.com/compare/mimo-v2-6-flash-rl-vs-qwen3-5-2b.md)
- [MiMo-V2.6-Flash-RL vs Qwen3.5-397B-A17B](https://www.anchorterminal.com/compare/mimo-v2-6-flash-rl-vs-qwen3-5-397b-a17b.md)
- [MiMo-V2.6-Flash-RL vs Qwen3.5-4B](https://www.anchorterminal.com/compare/mimo-v2-6-flash-rl-vs-qwen3-5-4b.md)
- [MiMo-V2.6-Flash-RL vs Qwen3.5-9B](https://www.anchorterminal.com/compare/mimo-v2-6-flash-rl-vs-qwen3-5-9b.md)
- [MiMo-V2.6-Flash-RL vs Qwen3.6-27B](https://www.anchorterminal.com/compare/mimo-v2-6-flash-rl-vs-qwen3-6-27b.md)
- [MiMo-V2.6-Flash-RL vs Qwen3.6-35B-A3B](https://www.anchorterminal.com/compare/mimo-v2-6-flash-rl-vs-qwen3-6-35b-a3b.md)
- [MiMo-V2.6-Flash-RL vs Qwen3.8-27B](https://www.anchorterminal.com/compare/mimo-v2-6-flash-rl-vs-qwen3-8-27b.md)
- [MiMo-V2.6-Flash-RL vs Qwen3.8-Flash-Next](https://www.anchorterminal.com/compare/mimo-v2-6-flash-rl-vs-qwen3-8-flash-next.md)
- [MiMo-V2.6-Flash-RL vs Qwen3-Coder-30B-A3B-Instruct](https://www.anchorterminal.com/compare/mimo-v2-6-flash-rl-vs-qwen3-coder-30b-a3b-instruct.md)
- [MiMo-V2.6-Flash-RL vs Qwen3-Coder-Next](https://www.anchorterminal.com/compare/mimo-v2-6-flash-rl-vs-qwen3-coder-next.md)
- [MiMo-V2.6-Flash-RL vs Qwen3-Omni-30B-A3B-Instruct](https://www.anchorterminal.com/compare/mimo-v2-6-flash-rl-vs-qwen3-omni-30b-a3b-instruct.md)
- [MiMo-V2.6-Flash-RL vs Qwen3-VL-2B-Instruct](https://www.anchorterminal.com/compare/mimo-v2-6-flash-rl-vs-qwen3-vl-2b-instruct.md)
- [MiMo-V2.6-Flash-RL vs Qwen3-VL-30B-A3B-Instruct](https://www.anchorterminal.com/compare/mimo-v2-6-flash-rl-vs-qwen3-vl-30b-a3b-instruct.md)
- [MiMo-V2.6-Flash-RL vs Qwen3-VL-32B-Instruct](https://www.anchorterminal.com/compare/mimo-v2-6-flash-rl-vs-qwen3-vl-32b-instruct.md)
- [MiMo-V2.6-Flash-RL vs Qwen3-VL-4B-Instruct](https://www.anchorterminal.com/compare/mimo-v2-6-flash-rl-vs-qwen3-vl-4b-instruct.md)
- [MiMo-V2.6-Flash-RL vs Qwen3-VL-8B-Instruct](https://www.anchorterminal.com/compare/mimo-v2-6-flash-rl-vs-qwen3-vl-8b-instruct.md)
- [MiMo-V2.6-Flash-RL vs Qwopus3.8-27B-Flash-V2](https://www.anchorterminal.com/compare/mimo-v2-6-flash-rl-vs-qwopus3-8-27b-flash-v2.md)
- [MiMo-V2.6-Flash-RL vs Recursive Flint](https://www.anchorterminal.com/compare/mimo-v2-6-flash-rl-vs-recursive-flint.md)
- [MiMo-V2.6-Flash-RL vs Ripple-65B Preview](https://www.anchorterminal.com/compare/mimo-v2-6-flash-rl-vs-ripple-65b-preview.md)
- [MiMo-V2.6-Flash-RL vs SenseNova-Loop-9B-Preview](https://www.anchorterminal.com/compare/mimo-v2-6-flash-rl-vs-sensenova-loop-9b-preview.md)
- [MiMo-V2.6-Flash-RL vs SmolLM3-3B](https://www.anchorterminal.com/compare/mimo-v2-6-flash-rl-vs-smollm3-3b.md)
- [MiMo-V2.6-Flash-RL vs Spark-X2.6-4B](https://www.anchorterminal.com/compare/mimo-v2-6-flash-rl-vs-spark-x2-6-4b.md)
- [MiMo-V2.6-Flash-RL vs Step 3.7 Flash](https://www.anchorterminal.com/compare/mimo-v2-6-flash-rl-vs-step-3-7-flash.md)
- [MiMo-V2.6-Flash-RL vs Swift 1.5 Qwen3.8-27B](https://www.anchorterminal.com/compare/mimo-v2-6-flash-rl-vs-swift-1-5-qwen3-8-27b.md)
- [MiMo-V2.6-Flash-RL vs Swift 1.5 Qwen3.8-Flash-Next](https://www.anchorterminal.com/compare/mimo-v2-6-flash-rl-vs-swift-1-5-qwen3-8-flash-next.md)
- [MiMo-V2.6-Flash-RL vs ThinkingCap (Qwen3.8 27B)](https://www.anchorterminal.com/compare/mimo-v2-6-flash-rl-vs-thinkingcap-qwen3-8-27b.md)
- [MiMo-V2.6-Flash-RL vs Baidu Unlimited-OCR-2](https://www.anchorterminal.com/compare/mimo-v2-6-flash-rl-vs-unlimited-ocr-2.md)
- [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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