deepseek-flash vs mimo-v2.6-flash
Parameters, independent leaderboard coverage, real-task reports and open-weight availability are shown side by side; missing coverage is not a zero.
Parameters
| Comparison item | deepseek-flash | mimo-v2.6-flash |
|---|---|---|
| Model Type | LLM | LLM |
| Context window | 1,000,000 tokens | — |
| Maximum output | 384,000 tokens | — |
| Input/output modalities | text, image → text | — |
| Endpoint | openai · openai-response · anthropic | openai · anthropic · openai-response |
| Open weights | Available | Available |
| License | MIT | MIT (declared in the model card metadata) |
Leaderboard coverage
Every independent board covering either model is retained; an em dash means that board has not published a figure for that model.
Real-task reports
deepseek-flash
- RemakeBench Launch 005: four Flash models on 14 fixtures — Fourteen fixtures spanning game building, 3D scenes, CAD, drawing and robot control, run on Qwen 3.8 Flash, DeepSeek V4.1 Flash, GLM 5.3 Flash and Gemini 3.8 Flash. Finding: No model won overall. DeepSeek V4.1 Flash delivered the best submitted Turbofan CAD result (three valid native solids, with a wrong-sign coupling and LP/HP interference) and did not pass the single-turn Rubik's Cube task. Limitation: Pass/fail labels are video judgments without a machine-readable validator, and single attempts do not establish reliability; the lab publishes no aggregate score or overall winner. Several DeepSeek clips reuse earlier records that keep V4 labels and the Vision exp setting; the two results quoted here are campaign runs added for this comparison.
- MiMo-V2.6-Flash, DeepSeek V4.1 Flash and Grok 4.7 on one game prompt — Build a playable browser game from a single prompt with Command Code's /design command. Finding: DeepSeek V4.1 Flash scored 9/10 for $0.0089 with a playable one-shot game. MiMo-V2.6-Flash also scored 9/10 at $0.005; Grok 4.7 scored 8/10 at $0.20 and needed iterations. Limitation: One prompt rated by the author, whose profile lists work for Command Code, the tool that ran the test; there is no rubric and no repeated run.
- DeepSeek V4.1 Flash and GLM 5.3 Flash recreating two game menus — Recreate the Psychonauts 2 and Metroid Prime main menus as closely as possible to the originals. Finding: DeepSeek V4.1 Flash used 412k and 466k tokens, three to four times GLM 5.3 Flash's 134k and 111k, and the author judged GLM's menus clearly better on both games. Limitation: Which menu is closer to the original is the author's own judgement on two prompts, without a scoring rubric.
- Switching a coding project from GPT-6 Astra to DeepSeek V4.1 Flash — Review an existing project, list its issues and fix them. Finding: DeepSeek V4.1 Flash found several issues, asked which to tackle first and began fixing them; Kimi's review still found problems, which were passed back to DeepSeek to correct. Limitation: One uncontrolled self-report. The author ran DeepSeek through WorkBuddy's free access, so the remark about spending nothing extra does not reflect API pricing.
- Step 5 Preview and DeepSeek V4.1 Flash on a 3D arcade game — Build Katamari Tiny, a 3D arcade game, from a single prompt. Finding: DeepSeek V4.1 Flash used 26,898 tokens against Step 5 Preview's 39,830 and, in the author's view, was faster and produced the better game. Limitation: One prompt judged by an author who names DeepSeek V4.1 Flash as their default model; the post gives no timings or quality rubric.
- DeepSeek V4.1 Flash and GLM-5.3-Flash on a Blender geometry task, run locally — Write a Blender script that builds a dodecahedron trapped inside a dodecahedron. Finding: Both models produced a correct mesh with zero intersections. DeepSeek V4.1 Flash took 20 min 15 s and 62,928 tokens at 51.8 tok/s, about a fifth of GLM-5.3-Flash's time and half its tokens, and its computed clearance matched the measured mesh (0.238); the author found GLM's picture nicer. Limitation: One local run per model on different hardware and precision: GLM ran as a third-party EXL3 quantisation on two DGX Sparks and DeepSeek as FP8 on four, so speed and token counts describe those builds, not the official weights or a hosted API.
- Three Flash models build the same koi pond locally — A koi pond build, run as a local head-to-head. Finding: All three finished cleanly with zero fixes. DeepSeek V4.1 Flash was fastest at 21 minutes and 53.3K tokens, a third of GLM-5.3-Flash's time, and the author ranked it first. Limitation: One local run per model; the post states neither the prompt nor the quantisation or runtime used.
- Step 5 Preview and DeepSeek V4.1 Flash on one Three.js scene — A Three.js scene of giant red mesas in a desert, with long shadows and a huge empty sky. Finding: DeepSeek V4.1 Flash's scene was more restrained but had clearly better ground and mesa textures and a smoother camera; Step 5 Preview added more atmosphere, a tracked sun, particle and dust effects and on-screen text. Limitation: One prompt judged by eye by the author; the post does not say how either model was accessed.
mimo-v2.6-flash
- MiMo-V2.6-Flash, DeepSeek V4.1 Flash and Grok 4.7 on one game prompt — Build a playable browser game from a single prompt with Command Code's /design command. Finding: MiMo-V2.6-Flash scored 9/10 for $0.005, the cheapest run, with a playable one-shot game. DeepSeek V4.1 Flash also scored 9/10 at $0.0089; Grok 4.7 scored 8/10 at $0.20 and needed iterations. Limitation: One prompt rated by the author, whose profile lists work for Command Code, the tool that ran the test; there is no rubric and no repeated run.
- A senior engineer's security and git tasks with MiMo-V2.6 Pro and Flash — Create a branch and cherry-pick one commit in a sandbox whose git worktree turned out to be corrupted. Finding: MiMo-V2.6-Flash spent about 80k tokens on risky workarounds such as tampering with /tmp and mount --bind instead of diagnosing or recovering the worktree; the author concludes it falls well short of its benchmark placement and stays with DeepSeek V4.1 Flash and Qwen3.8-Flash. Limitation: One task per model, with the serving provider, quantisation and settings not stated; the post's title calls the series benchmaxxed.
- Three Flash models build the same koi pond locally — A koi pond build, run as a local head-to-head. Finding: All three finished cleanly with zero fixes; MiMo-V2.6-Flash took 30 minutes and 75.5K tokens, between DeepSeek V4.1 Flash (21 minutes, 53.3K) and GLM-5.3-Flash (59 minutes, 90.9K). Limitation: One local run per model; the post states neither the prompt nor the quantisation or runtime used.
- MiMo-V2.6-Flash on page and SVG tasks and a real app bug fix — Build pages explaining Chinese bagua culture and how a thorium molten-salt reactor works, draw Schrödinger's cat as an SVG, and fix a real bug in the author's app. Finding: The pages and SVGs were the best the author had seen, scoring 85–95 (the bagua page 95, against about 90 for DeepSeek's page in an earlier test), and all the tasks together cost about $0.50; but the bagua page took at least five times as long as DeepSeek's, the first attempt at it failed after 10–20 minutes, and a simple app bug fix stalled for an hour on tool-call errors. Limitation: One author's scores on a handful of tasks; the DeepSeek comparison rests on the author's earlier runs and estimates, and the author expects Xiaomi may fix the speed and tool-call problems.
- A MiMo-V2.6-Flash game build that needed steering — A browser game build the author meant to run zero-shot. Finding: The model thought for more than 11 minutes and got stuck in an overthinking loop while writing the file, so the author had to steer it several times; the result was solid, cost about $0.05, and scored 9.5/10 from the author, who said it did not feel like a Flash model for speed. Limitation: One task with several manual interventions, which the author says means it may not reflect what the model would produce on its own; the score is the author's.