Kimi K3.1 Pro vs GPT-6 Astra
Kimi K3.1 Pro scores higher on the Models at Work leaderboard (86 vs 82 out of 100). Kimi K3.1 Pro is about 5.0× cheaper per blended million tokens ($4 vs $20). On Artificial Analysis' independent Intelligence Index, Kimi K3.1 Pro leads 55 to 53.
| Kimi K3.1 Pro · Moonshot | GPT-6 Astra · OpenAI | |
|---|---|---|
| Leaderboard rank | #2 | #5 |
| Score (0–100) | 86 | 82 |
| Tier | Open weights | Frontier |
| Price per 1M tokens | $2 in · $10 out | $10 in · $50 out |
| Context window | 1M | 1M |
| Open weights | Yes | No |
| Artificial Analysis Intelligence Index | 55 | 53 |
| Terminal-Bench 4.0 (vendor) | 65.7% | — |
| Humanity's Last Exam, Diamond (Scale) | — | 60.6 |
| Humanity's Sixth Sense (Scale) | — | 53.6 |
| FrontierMath Erdős (Epoch) | — | 3% (2 of 68) |
| Best for | Agentic coding with an open-weight exit, 1M-token long-context work, Moving off Kimi K3 | Hard reasoning, Research-grade analysis, When cost is not the constraint |
Compare source-qualified API rates and a monthly workload example before estimating your bill.
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.
Choose GPT-6 Astra if…
- you need hard reasoning
- you need research-grade analysis
- you need when cost is not the constraint
The reasoning heavyweight: leads the hardest exams and the cipher-cracking party tricks, and charges like it.
Caveats: Long-context pricing doubles above 272K input tokens. Speed is the lowest of the frontier set in Artificial Analysis' measurement.
What practitioners say
Kimi K3.1 Pro: No practitioner threads recorded in Signals yet; left out of the score rather than guessed.
GPT-6 Astra: The launch drew the largest model thread of 2026 on Hacker News, and the stories that followed were about capability rather than cost: an Enigma message unsolved since 2005, a WWI cipher, a driving benchmark.
Questions people ask
Which is better, Kimi K3.1 Pro or GPT-6 Astra?
Kimi K3.1 Pro scores higher on the Models at Work leaderboard (86 vs 82 out of 100). Kimi K3.1 Pro is about 5.0× cheaper per blended million tokens ($4 vs $20). On Artificial Analysis' independent Intelligence Index, Kimi K3.1 Pro leads 55 to 53.
When should I choose Kimi K3.1 Pro over GPT-6 Astra?
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.
When should I choose GPT-6 Astra over Kimi K3.1 Pro?
Choose GPT-6 Astra for hard reasoning, research-grade analysis, when cost is not the constraint. The reasoning heavyweight: leads the hardest exams and the cipher-cracking party tricks, and charges like it.
Which is cheaper, Kimi K3.1 Pro or GPT-6 Astra?
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). GPT-6 Astra costs $10 per million input tokens and $50 per million output tokens on OpenAI's list price (OpenAI API 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.