Claude Sonnet 5.5 vs Kimi K3.1 Pro
Claude Sonnet 5.5 and Kimi K3.1 Pro are within three points on the Models at Work leaderboard, which we treat as a tie (86 vs 86). They cost about the same per million tokens ($4 vs $4 blended). On Artificial Analysis' independent Intelligence Index, Claude Sonnet 5.5 leads 56 to 55.
| Claude Sonnet 5.5 · Anthropic | Kimi K3.1 Pro · Moonshot | |
|---|---|---|
| Leaderboard rank | #1 | #2 |
| Score (0–100) | 86 | 86 |
| Tier | Workhorse | Open weights |
| Price per 1M tokens | $2 in · $10 out | $2 in · $10 out |
| Context window | 1M | 1M |
| Open weights | No | Yes |
| Artificial Analysis Intelligence Index | 56 | 55 |
| Terminal-Bench 4.0 (vendor) | — | 65.7% |
| Best for | Production coding assistants, High-volume agents, Default model for most teams | Agentic coding with an open-weight exit, 1M-token long-context work, Moving off Kimi K3 |
Compare source-qualified API rates and a monthly workload example before estimating your bill.
Choose Claude Sonnet 5.5 if…
- you need production coding assistants
- you need high-volume agents
- you need default model for most teams
The value pick of the table: second on the index at a fifth of the Opus price, and the fastest of the top five.
Choose Kimi K3.1 Pro if…
- you need agentic coding with an open-weight exit
- you need 1m-token long-context work
- you need moving off kimi k3
Fourth on the Artificial Analysis index at 55, one point behind Sonnet 5.5, at the same $2 in / $10 out list price, with the weights still to come.
Caveats: Scores within three points of Sonnet 5.5 (tie), and ranks on evals and price alone because no practitioner sentiment exists yet. Moonshot says the full weights arrive by 4 Nov 2026; until then it is open-weight in intent, hosted-only in practice. Artificial Analysis rates it slow (51 tokens/s) and very verbose: 150M tokens to run its index, which is where the $2.11 per-task cost comes from. Moonshot's Terminal-Bench figure is vendor-run and is not counted. No Arena or Scale result yet, and no practitioner threads in Signals, so sentiment is left out.
What practitioners say
Claude Sonnet 5.5: Less discussed than its siblings because it just works; the October cache-read price cut to $0.10 per million was the news.
Kimi K3.1 Pro: No practitioner threads recorded in Signals yet; left out of the score rather than guessed.
Questions people ask
Which is better, Claude Sonnet 5.5 or Kimi K3.1 Pro?
Claude Sonnet 5.5 and Kimi K3.1 Pro are within three points on the Models at Work leaderboard, which we treat as a tie (86 vs 86). They cost about the same per million tokens ($4 vs $4 blended). On Artificial Analysis' independent Intelligence Index, Claude Sonnet 5.5 leads 56 to 55.
When should I choose Claude Sonnet 5.5 over Kimi K3.1 Pro?
Choose Claude Sonnet 5.5 for production coding assistants, high-volume agents, default model for most teams. The value pick of the table: second on the index at a fifth of the Opus price, and the fastest of the top five.
When should I choose Kimi K3.1 Pro over Claude Sonnet 5.5?
Choose Kimi K3.1 Pro for agentic coding with an open-weight exit, 1m-token long-context work, moving off kimi k3. Fourth on the Artificial Analysis index at 55, one point behind Sonnet 5.5, at the same $2 in / $10 out list price, with the weights still to come.
Which is cheaper, Claude Sonnet 5.5 or Kimi K3.1 Pro?
Claude Sonnet 5.5 costs $2 per million input tokens and $10 per million output tokens on Anthropic's list price (Claude pricing, read Oct 26, 2026). Kimi K3.1 Pro costs $2 per million input tokens and $10 per million output tokens on Moonshot's list price (Kimi API model pricing, read Oct 26, 2026).
Scores come from the Models at Work leaderboard: Score is 0 to 100 and computed, not typed: 55% independent evals (Artificial Analysis, Arena, Scale SEAL, Epoch, each scaled against its natural floor and the best score in this table, then averaged), 15% blended price on a fixed log scale ($0.05 per million is 100, $60 is 0), 15% practitioner sentiment from Signals and community threads, 15% operational fit (context window, open weights). A missing component drops out and the rest are reweighted. A model with no independent eval yet is provisional and ranks below every measured one. Within three points is a tie. Vendor-published figures are labelled and never counted. Prices are vendor list prices where published; blended figures assume three input tokens per output token.