Kimi K2.7 Code is Moonshot's cheapest model at $0.95/1M input tokens — 68% less than the flagship Kimi K3. It is also the best capability-per-dollar pick in the lineup.
The shortest way to see the safest default, the lower-cost option, and the specialist pick before you read deeper.
Kimi K2.7 Code is the safest overall answer here when you want the strongest default instead of the lowest list price.
Mistral: Mistral Nemo is the lower-cost option to start with when you still need useful output at scale.
Kimi K3 is the better pick when response speed matters more than maximum reasoning depth.
Kimi K2.7 Code is the lowest-cost Moonshot model: $0.95/1M input, $4/1M output.
Kimi K2.7 Code is the best capability-per-dollar pick (budget score 85/100).
Kimi K3 costs 3x more on input — reserve it for work where quality is the bottleneck.
Choose Kimi K2.7 Code for high-volume, low-stakes tasks like classification, extraction, and drafts.
Choose Kimi K2.7 Code as the everyday default if you want one budget model.
Route only the hardest tasks to Kimi K3 — a two-tier setup usually cuts spend 60–80%.
Switch the scoring lens to see whether the top answer changes when you care more about cost, speed, or long-document work.
Moonshot / Premium / Aug 6, 2026
Closest Chinese challenger to the frontier — #4 overall on intelligence.
Ranks models by the broadest mix of coding, writing, research, and long-context usefulness.
You need fast responses or predictable output costs — always-on thinking burns tokens.
The fastest way to see where the recommendation shifts when your priority changes.
Value coding specialist — 1T MoE agentic coder at budget prices.
Closest Chinese challenger to the frontier — #4 overall on intelligence.
Every figure below is the provider's list price or a published capability score — the same numbers the recommendation on this page is built from.
| Model | Input | Output | Est. month | Context | Speed | Coding | Writing | Research |
|---|---|---|---|---|---|---|---|---|
| Kimi K2.7 CodeMoonshot | $0.95/1M | $4.00/1M | $18 | 256k tokens | Fast | 88 | 68 | 70 |
| Kimi K3Moonshot | $3.00/1M | $15.00/1M | $60 | 1M tokens | Deliberate | 96 | 90 | 93 |
Capability scores are out of 100 and reflect our own weighting of published benchmarks and production signals — see how we evaluate models. “Est. month” assumes 10M input and 2M output tokens at list price, with no batch or caching discounts applied, so treat it as a ceiling.
What each one is genuinely good at, where it falls down, and the situations we would steer you away from it — not just the headline score.
An open-weight 1T-parameter MoE (32B active) coding specialist tuned for long-horizon agentic software engineering with markedly better token efficiency than its predecessor.
Your agent needs big-repo context (256K cap) or frontier general reasoning.
The value pick among coding specialists. K3 superseded it at the frontier a month later, but for pure coding-agent volume at a quarter of K3's input price, K2.7 Code remains the smarter buy.
Model ID kimi-k2.7-code; weights on Hugging Face June 12, 2026. Kimi Code membership from $19/mo.
Moonshot's 2.8-trillion-parameter multimodal reasoning flagship with always-on thinking — the largest open-weight model ever released and the closest Chinese challenger to the Western frontier.
You need fast responses or predictable output costs — always-on thinking burns tokens.
The first Chinese model to genuinely crowd the Western frontier — #4 on aggregate intelligence ahead of Opus 4.8. The always-on thinking makes it slow and output-heavy, so cost per task runs above the sticker price. A serious Opus-class alternative if latency isn't critical.
Released July 16, 2026; open weights July 26. Cache-hit input $0.30/1M. Subscriptions: Adagio (free) to Vivace $199/mo; full 1M context only on Allegro ($99) and up. New signups paused July 19 near GPU capacity, reopening in batches.
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Kimi K2.7 Code at $0.95/1M input and $4/1M output tokens. Value coding specialist — 1T MoE agentic coder at budget prices.
Kimi K2.7 Code is the best capability-per-dollar pick in Moonshot's lineup (budget score 85/100). It handles cost-efficient agentic coding well — step up to Kimi K3 only where quality visibly falls short.
Kimi K2.7 Code costs $0.95/1M input vs $3/1M for Kimi K3 — a 68% saving on input tokens.
Kimi K3 — 1M tokens at $3/1M input. Context is where budget models are least compromised: you usually lose reasoning depth before you lose window size, so a cheap model is often a perfectly good choice for summarising or extracting from long documents.
256K context is a quarter of what 2026 rivals offer for large-repo agent work. Headline gains are on Moonshot's own in-house benchmark; general reasoning lags the Western frontier. Avoid it if your agent needs big-repo context (256K cap) or frontier general reasoning.
On a moderate workload of 10M input and 2M output tokens, Kimi K2.7 Code runs about $17.50 against $60.00 for Kimi K3 — a difference of $42.50 a month at the same volume. Output tokens dominate the bill on both, so the length of the responses you generate matters far more than the length of your prompts.
Mixing is almost always cheaper for the same quality. Route high-volume, low-stakes work — classification, extraction, first drafts, routine agent steps — to Kimi K2.7 Code, and reserve Kimi K3 for the calls where a wrong answer costs real time. Teams that split this way typically cut spend substantially without a quality drop anyone notices, because most tokens in a real workload are not hard problems.