Anthropic Claude Sonnet 5 (1M) vs Moonshot Kimi K3.7 Mini (256k)
Side-by-side comparison of pricing, context window, capabilities, and a real-cost sample workload.
Option A
Anthropic Claude Sonnet 5 (1M)
by Anthropic
Context:1M
Input:$3.00 / 1M
Output:$15.00 / 1M
Released:2026-07
Option B
Moonshot Kimi K3.7 Mini (256k)
by Moonshot AI
Context:256K
Input:$0.15 / 1M
Output:$0.80 / 1M
Released:2026-07
Detailed Comparison
| Dimension | Anthropic Claude Sonnet 5 (1M) | Moonshot Kimi K3.7 Mini (256k) |
|---|---|---|
| Provider | Anthropic | Moonshot AI |
| Context window Winner | 1M | 256K |
| Input price ($/1M) Winner | $3.00 | $0.15 |
| Output price ($/1M) Winner | $15.00 | $0.80 |
| Sample workload cost Winner 1M input + 500K output tokens | $10.50 | $0.55 |
| Released TieTie | 2026-07 | 2026-07 |
| Tokenizer | claude-4 | kimi |
The verdict
On the dimensions we measured, Moonshot Kimi K3.7 Mini (256k) wins more often - particularly on cost-effectiveness for a typical 1M+0.5M workload.
Anthropic Claude Sonnet 5 (1M) - Key features
The workhorse of the Claude 5 family. Sonnet 5 lands close to Opus 4.8 on coding and agentic benchmarks while staying at the long-standing Sonnet price, with a 1M token context window available by default.
- 1M token context window
- Near-Opus coding quality
- Fast time to first token
- Strong tool use and structured output
- Batch and caching discounts
Moonshot Kimi K3.7 Mini (256k) - Key features
A distilled K3.7 aimed at classification, extraction and sub-agent duty. Runs comfortably on a single high-memory GPU when self-hosted.
- Distilled from K3.7
- 256K token context window
- Single-GPU friendly
- Very low cost
- Open weights
How to choose
- Pick the cheaper model if your workload is mostly straightforward classification, extraction, or summarization.
- Pick the bigger context if you process long documents, large codebases, or multi-document research.
- Pick the more recent release if you need state-of-the-art reasoning quality and don't mind paying a bit more.
- Use both via a routing layer - send simple tasks to the cheaper one and complex tasks to the smarter one. This is the highest-ROI optimization in production AI.
Estimate the real cost of either model for your prompts using our Token Calculator.