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Model comparison - Similar price, same tier

Kimi K2.7 Code vs Mistral Large 4

Kimi K2.7 Code is from Moonshot AI and Mistral Large 4 is from Mistral AI. On list price, Kimi K2.7 Code charges 30% less than Mistral Large 4 for input ($0.95 vs $1.36 per 1M tokens), and Kimi K2.7 Code charges 4% less than Mistral Large 4 for output ($4 vs $4.18 per 1M tokens). Kimi K2.7 Code has a 262,144-token context window and Mistral Large 4 1,000,000 tokens. Mistral Large 4 was released on October 5, 2026; no primary source states a release date for Kimi K2.7 Code. Kimi K2.7 Code publishes open weights (Modified MIT License (Hugging Face license tag: other)); Mistral Large 4 is closed-weights.

Last verified from each provider's pricing page. All sources

Moonshot AI - Open

Kimi K2.7 Code
Input / 1M
$0.95
Output / 1M
$4
Context
262K

Mistral AI - Closed

Mistral Large 4
Input / 1M
$1.36
Output / 1M
$4.18
Context
1M

Side-by-side specs

SpecKimi K2.7 CodeMistral Large 4
ProviderMoonshot AIMistral AI
Input / 1M tokens$0.95$1.36
Output / 1M tokens$4$4.18
Cache read / 1M$0.19$0.14
Batch input / 1M$0.57$0.68
Batch output / 1M$2.40$2.09
Context window262,1441,000,000
Release date-
WeightsOpenClosed
LicenseModified MIT License (Hugging Face license tag: other)-
API model idkimi-k2.7-codemistral-large-4
AI Gateway idmoonshotai/kimi-k2.7-codemistral/mistral-large-4
Last verified

Prices in USD per 1M tokens at each provider's standard first-party rate. A dash means the provider does not bill that item separately or no primary page states it.

What each costs in practice

The same three workloads every model page uses, worked from each model's standard list rates. Swap in your own token counts with the math on each model's page.

WorkloadKimi K2.7 CodeMistral Large 4
One agent session1M input tokens and 100K output tokens, no caching.$1.35$1.78
A chat app10,000 requests a day at 2K input and 500 output tokens each.$39.00$1,170.00 per 30-day month$48.10$1,443.00 per 30-day month
The same session at a 90% cache hit90% of the input is read from the prompt cache. The one-time cache write premium is not included.$0.666$0.68
Show the math

Kimi K2.7 Code

  • One agent sessionInput: 1M x $0.95 = $0.95Output: 0.1M x $4 = $0.40
  • A chat appInput: 20M x $0.95 = $19.00Output: 5M x $4 = $20.00
  • The same session at a 90% cache hitCached input: 0.9M x $0.19 = $0.171Uncached input: 0.1M x $0.95 = $0.095Output: 0.1M x $4 = $0.40

Mistral Large 4

  • One agent sessionInput: 1M x $1.36 = $1.36Output: 0.1M x $4.18 = $0.418
  • A chat appInput: 20M x $1.36 = $27.20Output: 5M x $4.18 = $20.90
  • The same session at a 90% cache hitCached input: 0.9M x $0.14 = $0.126Uncached input: 0.1M x $1.36 = $0.136Output: 0.1M x $4.18 = $0.418

Benchmarks under the same setting

No board in the benchmark directory lists both Kimi K2.7 Code and Mistral Large 4 under the same setting, so there is no like-for-like score to show here.

Set them up in your tools

Step-by-step guides whose official docs list Kimi K2.7 Code or Mistral Large 4 by model id.

Model pages

FAQ

How do Kimi K2.7 Code and Mistral Large 4 compare on price?

On list price, Kimi K2.7 Code charges 30% less than Mistral Large 4 for input ($0.95 vs $1.36 per 1M tokens), and Kimi K2.7 Code charges 4% less than Mistral Large 4 for output ($4 vs $4.18 per 1M tokens). For one agent session of 1M input and 100K output tokens with no caching, that is $1.35 on Kimi K2.7 Code and $1.78 on Mistral Large 4. Prices are each provider's first-party list rates, verified October 17, 2026 and October 17, 2026.

What are the context windows of Kimi K2.7 Code and Mistral Large 4?

Kimi K2.7 Code has a 262,144-token context window and Mistral Large 4 1,000,000 tokens.

Are Kimi K2.7 Code and Mistral Large 4 open weights?

Kimi K2.7 Code's weights are published at huggingface.co under the Modified MIT License (Hugging Face license tag: other). Mistral Large 4 is closed-weights and is called through Mistral AI's API as mistral-large-4.

More comparisons

Sources

Kimi K2.7 Code verified from platform.kimi.ai; Mistral Large 4 verified from docs.mistral.ai. This page is as current as the older of the two: .

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