DeepSeek-V3.2 vs MiMo-V2.6-Flash-RL

DeepSeek-V3.2 60

The chat template earns 10, as the format exists only as Python code to run. The tool-calling format earns 10 because DeepSeek documents the DSML format in code but names no runtime parser, which only vLLM's own recipe does. Trained tool calling earns the full 20 for several calls in one block. Structured output earns nothing, as JSON output isn't documented. Reasoning control earns 10 for thinking or chat mode per request with reasoning_content returned. Context earns 10 for 128K trained tokens.

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.

DeepSeek-V3.2 34

The model card earns 14 when read with DeepSeek's own V3.2 model card PDF, which adds intended use and a parameter count, leaving languages and a knowledge cut-off missing. Training data earns 5, a general description with no cut-off. Last change earns 5, as nothing in the repository has changed since 1 December 2025 (338 days on 4 November) and DeepSeek's deepseek-recipe has no V3.2 code. Responsiveness earns nothing, with no reply from a deepseek-ai member in any of the 40 most recent discussions. Version policy earns 5 for earlier versions kept apart without dated notes. File health earns 5 because loading and parsing reports wait without a reply.

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.

DeepSeek-V3.2 60

Memory earns nothing, because the only build from DeepSeek or a runtime's library is the 689.5 GB FP8 release, which needs about 827 GB with the fifth added. Runtimes earn the full 25 for released model code in vLLM, SGLang, llama.cpp and Transformers, and for Ollama 0.40.14, whose llama.cpp pin (b11963) carries the deepseek32 architecture with no gate in Ollama's server code, though its library entry stays retired; nothing from LM Studio. Builds earn 10 for the single FP8 precision DeepSeek publishes. Terms earn the full 15 for MIT with nothing added, and download the full 10 since the repository isn't gated. Hosted earns nothing, since DeepSeek's own API moved to V4 on 24 April 2026 and Hugging Face maps only DeepInfra as live for it on 4 November (Novita and Featherless in error), where the line needs two providers. Fireworks' model page says Serverless Not Supported and lists it only for on-demand deployment on dedicated GPUs, which is renting the hardware rather than calling a served model.

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.

DeepSeek-V3.2 50

File safety earns 15, safetensors only but 10 off because prompts are built by running DeepSeek's Python from the repository. Provenance earns the full 15 for the deepseek-ai organisation and a SHA-256 on every shard. Safety evaluation earns nothing, since no results are published anywhere. Agent guidance earns nothing, since the notes about the parser and the developer role are usage notes, read alike for all three DeepSeek listings. Licence risk keeps the full 15 for plain MIT. The security programme earns 5 for the security@deepseek.com reporting address on DeepSeek's site, with no public advisories.

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.