MiMo-V2.6 Pro vs Kimi K2.7 · No-Think

What I tested — same prompt, two models

I run the same fixed prompt set through every new model the day it drops — same string, one shot, single HTML file out — and I score the result 0–10 on whether it ran, how close it hit the brief, and how good it looked. Below is what came out when I gave the exact same prompts to MiMo-V2.6 Pro and Kimi K2.7 · No-Think, side by side, on 47 shared tasks inside the Agent Operating System.

Both models were given identical prompts inside the Agent Operating System — no help, no iteration, no "best of N" tricks. I run each prompt once, save the HTML file the model produces, and score it 0–10 on whether it ran, how close it hit the brief, and how good it looked. The scoring is mine. The verdicts below are pulled from my source comparison guides at agentos.guide where I publish every score and the reasoning behind it.

MiMo-V2.6 Pro · Benched on all 50 GoldieBench tasks through OpenRouter at the model's default reasoning effort: one-shot build, real rendered poster, Opus 4.8 vision judge, game tasks skill-infused. No retries, no hand fixes; the broken builds are scored as they shipped.

Kimi K2.7 · No-Think · Reserved for templated transforms where the plan is already in the prompt — the model just executes.

Strengths & weaknesses I logged

Pricing & context — the spec sheet

The verdict — which should you pick?

Not enough scored shared tasks yet for a head-to-head average. The live demos for both are on the matrix above — play them and form your own opinion.

If you only run one of these inside your stack, the head-to-head average above is the call. If you can run both, my honest play is to wire MiMo-V2.6 Pro and Kimi K2.7 · No-Think both into the Agent Operating System and dispatch each from the kanban by task type — simulations, shaders and visual scenes in one shot, at a fraction of frontier prices → MiMo-V2.6 Pro, templated transforms where the plan is in the prompt → Kimi K2.7 · No-Think. That's the same setup I run for the 4,000+ founders inside the AI Profit Boardroom.

FAQ — MiMo-V2.6 Pro vs Kimi K2.7 · No-Think

Which is better, MiMo-V2.6 Pro or Kimi K2.7 · No-Think?

On Goldie Bench, MiMo-V2.6 Pro averages no scored verdicts yet across the shared tasks, with 5 gold, 8 silver, 4 bronze overall. Kimi K2.7 · No-Think averages no scored verdicts yet, with 0 gold, 0 silver, 0 bronze. Not enough scored shared tasks yet to call a winner.

How much does MiMo-V2.6 Pro cost vs Kimi K2.7 · No-Think?

MiMo-V2.6 Pro: Xiaomi's September 2026 open-weight flagship (MIT licence, 1.02T total / 42B active parameters). $0.435 per million input tokens and $0.87 per million output on OpenRouter, with cache hits at a fraction of a cent, which is roughly a quarter of Grok 4.7 and a twentieth of the closed frontier models it scores level with on agent benchmarks. Kimi K2.7 · No-Think: Same flat-rate plan as standard Kimi K2.7 — No-Think disables the chain-of-thought layer at runtime. Vendor: Moonshot AI (moonshot.ai).

What's the context window for MiMo-V2.6 Pro vs Kimi K2.7 · No-Think?

MiMo-V2.6 Pro has a 1,000,000 tokens context window. Kimi K2.7 · No-Think has a 256,000 tokens context window.

When should I pick MiMo-V2.6 Pro over Kimi K2.7 · No-Think?

Pick MiMo-V2.6 Pro for: Simulations, shaders and visual scenes in one shot, at a fraction of frontier prices; High-volume agent work where an open, MIT-licensed model matters; Pair it with a self-fix loop for games: the failures are single broken tokens, not missing ideas. The trade-off is the weaknesses we logged on the bench: 18 of 50 builds scored under 5: long game files shipped with garbled tokens (a stray 'martin' or 'martial' identifier breaks the whole script), uninitialised references and bad canvas values, so the HUD paints but the 3D scene stays black; Two hard crashes: the RPG threw an engine fault on load and the solar system rendered nothing at all; It reasons for a long time at default effort: builds took 5 to 60 minutes each through OpenRouter.

When should I pick Kimi K2.7 · No-Think over MiMo-V2.6 Pro?

Pick Kimi K2.7 · No-Think for: Templated transforms where the plan is in the prompt; Batched code generation jobs; Workflows where you want the model to stop second-guessing. The trade-off is the weaknesses we logged on the bench: Loses ground on multi-step tasks that benefit from planning; Not scored on the standalone bench — see methodology.

How does Goldie Bench score MiMo-V2.6 Pro vs Kimi K2.7 · No-Think?

Every demo on this page was built by Julian Goldie inside the Agent Operating System — same fixed prompt for both models, one shot, single HTML file out. Each result gets a 0–10 score on whether it ran, how close it hit the brief, and how good it looked. The highest score on each task gets gold; second gets silver; third gets bronze. See methodology for full provenance.

Related comparisons

Other head-to-heads using the same scoring system:

Full model pages: MiMo-V2.6 Pro · Kimi K2.7 · No-Think · back to the leaderboard