Updated 2026-10-27
Kimi K3 vs. Claude
Compare Kimi K3/K3.1 Pro with Claude Opus 5.5: 1M context, token prices, Terminal-Bench coding results, agents, and clear recommendations.
TL;DR
- Pick Kimi K3.1 Pro if you want lower Kimi list pricing, 1M context, open weights promised before Nov 4, and strong long-agent/coding value.
- Pick Claude Opus 5.5 if you want the higher published Terminal-Bench score, mature Claude ecosystem tooling, and predictable USD pricing.
- The closest published coding result is narrow: Claude Opus 5.5 66.4% vs Kimi K3.1 Pro 65.7% on Terminal-Bench 4.0.
- Kimi K3 remains useful for released-weight compatibility testing, but K3.1 Pro is both cheaper and stronger in official Kimi comparisons.
Side-by-side comparison
| Dimension | Kimi K3 | Kimi K3.1 Pro | Claude Opus 5.5 |
|---|---|---|---|
| Context window | 1,048,576 tokens | 1,048,576 tokens | 1M tokens |
| Input / MTok | ¥20 | ¥13 | $4 |
| Output / MTok | ¥100 | ¥68 | $20 |
| Cache-hit input / MTok | ¥2 | ¥1.30 | See Anthropic pricing page |
| Terminal-Bench 4.0 | Not published in cited table | 65.7% | 66.4% |
| Model positioning | Released previous flagship | Current flagship; weights promised before Nov 4 | Long-running agentic coding and knowledge work |
Coding and terminal agents
Moonshot's K3.1 Pro documentation reports 65.7% on Terminal-Bench 4.0, while Claude Opus 5.5 reports 66.4% and GPT-6 Astra 58.2%. The Kimi–Claude gap is only 0.7 percentage points, so coding-agent setup, tool permissions, retry policy, and context management can easily change the winner.
For long engineering sessions, K3.1 Pro also reports 61.2% on Kimi Code Bench 3.0 Long-horizon versus 55.95% for K3. Claude users should run the same repository task at their preferred effort level rather than relying only on vendor summaries.
Agentic workflows and tool use
Both model families support tool calling. Kimi K3/K3.1 Pro can use custom tools, dynamic tool definitions, structured JSON output, and Formula-hosted official tools. Claude's current model family supports adaptive thinking, tool use, vision, multilingual work, and server tools through its platform.
The practical differentiator is less 'can it call a tool' and more reliability over many steps: whether state is replayed correctly, whether failed calls are retried, how often the model changes arguments, and how much context each step consumes. Log those fields before choosing.
Long context and pricing
Kimi K3, K3.1 Pro, and current Claude models all expose a 1M-token context window, so context length alone is no longer a differentiator. Cost and cache behavior matter more.
Kimi's published cache-hit input price is ¥2/MTok for K3 and ¥1.30/MTok for K3.1 Pro. Claude publishes prompt caching separately; compare the exact cache-read, cache-write, base-input, and output rates for your region and provider.
Final recommendation
- High-volume coding agents on a CNY billing path: start with K3.1 Pro, cap completion tokens, and measure pass@1 plus total cost.
- Claude-centric workflow or highest published Terminal-Bench score: start with Claude Opus 5.5.
- Self-hosting or open-weight research: wait for the K3.1 Pro weights or use already released K3 weights.
- Simple short prompts: benchmark a smaller Claude/Kimi model first; flagship reasoning models may be overkill.
Frequently asked questions
Is Kimi K3 better than Claude?
There is no blanket winner. Moonshot's newer K3.1 Pro scores 65.7% on Terminal-Bench 4.0, slightly below Claude Opus 5.5 at 66.4%, but K3.1 Pro has lower Kimi list token prices and a 1M-token context. Test your own coding-agent tasks.
Is Kimi K3 cheaper than Claude?
Kimi K3 lists at ¥20/MTok input and ¥100/MTok output; K3.1 Pro lists at ¥13/MTok input and ¥68/MTok output. Claude Opus 5.5 lists at $4/MTok input and $20/MTok output. Currency, cache behavior, and output length determine the real monthly cost.
Which is better for coding agents?
Claude Opus 5.5 has the highest cited Terminal-Bench 4.0 score at 66.4%, while Kimi K3.1 Pro is close at 65.7% and reports a strong 61.2% long-horizon coding score. Run both on the same repository, tool set, timeout, and retry budget.