MiniMax M3 vs Kimi K2.5

Design Arena: M3 leads on every shared category

Across the eight "models" categories both are scored on, MiniMax M3 has the higher elo in all eight: 3d (1306 vs 1286), asciiart (1219 vs 1214), codecategories (1306 vs 1286), dataviz (1295 vs 1270), gamedev (1287 vs 1272), svg (1250 vs 1210), uicomponent (1291 vs 1290), and website (1304 vs 1291). Some of these are close — uicomponent is a 1-point elo gap — but M3 doesn't lose a single one on this metric. Kimi K2.5's win_rate numbers look competitive in a few spots (57.8% in androidnative, for example), but win_rate and elo aren't measuring the same thing, and elo is the head-to-head signal. If your workload maps to any of these eight categories, M3 is the safer default.

Where K2.5 has data M3 doesn't: agent arenas

K2.5 reports Design Arena scores in the "agents" arena for androidnative (elo 1132, rank 17), fullstack (1182, rank 14), godotgamedev (1254, rank 2), mobileapps (1186, rank 20), and webapps (1194, rank 15). M3 only has one agents-arena data point (androidnative, elo 990, rank 27) — and on that single overlapping category, K2.5 wins clearly (1132 vs 990). If your use case is closer to building and shipping an app end to end than generating a single code artifact, K2.5's broader agent-arena coverage and its godotgamedev rank-2 result are worth weighing even though M3 wins the model-category comparisons.

Pricing math

Provider list price: M3 runs $0.30/M input, $1.20/M output. K2.5 runs $0.375/M input, $2.025/M output. On OpenKey, both get the flat 3% fee added: M3 becomes $0.309/M input and $1.236/M output; K2.5 becomes $0.38625/M input and $2.08575/M output. For a 10M-input / 2M-output workload, M3 costs $5.40 total and K2.5 costs $7.80 — M3 is about 31% cheaper on that mix. The bigger delta is on output, where K2.5 runs nearly 69% higher per token than M3.

Context and output ceiling

M3 supports a 1,048,576-token context window against K2.5's 262,144 — a 4x ratio. M3 also lists a 512,000-token max completion, while K2.5 has no max_completion_tokens value in its record. If you're processing long documents, large codebases, or multi-file repos in a single call, M3's window gives you room K2.5 doesn't have. K2.5's default_enabled reasoning mode is turned on out of the box; M3's reasoning is optional but not mandatory either way, so you control the tradeoff on both.

When to pick each

Pick M3 for straight code generation, UI or design-artifact tasks, or any job where you need the largest context window at the lowest cost — it wins the model-category benchmarks and costs less per token on both ends. Pick K2.5 when the job looks like an agent swarm hitting a real target (a mobile app, a full-stack build, a Godot project) since that's where it has benchmark coverage and M3 mostly doesn't. Both run on OpenKey through one API key with the same flat 3% fee on top of provider list price, so switching between them for A/B testing on a workload is a config change, not a new integration.

Questions

Is MiniMax M3 cheaper than Kimi K2.5?

Yes. On OpenKey, M3 runs $0.309/M input and $1.236/M output; K2.5 runs $0.38625/M input and $2.08575/M output. A 10M-input/2M-output workload costs $5.40 on M3 versus $7.80 on K2.5 — roughly 31% less.

Which model has the bigger context window?

MiniMax M3, by a factor of 4. M3 supports 1,048,576 tokens versus K2.5's 262,144. M3 also lists a 512,000-token max completion; K2.5 has no max_completion_tokens value recorded.

Does Kimi K2.5 beat M3 on any Design Arena benchmark?

M3 leads all eight shared model-category elo scores (3d, asciiart, codecategories, dataviz, gamedev, svg, uicomponent, website). K2.5's edge shows up in the agents arena, where it beats M3's one overlapping score (androidnative: 1132 vs 990) and has four agent categories M3 doesn't report at all.

Which model should I use for an agent swarm building a mobile app?

Kimi K2.5. It reports Design Arena agents-arena scores for mobileapps (elo 1186, rank 20) and androidnative (elo 1132, rank 17), and M3 only has one comparable agents-arena entry, which K2.5 beats by 142 elo points.