Kimi K3.1 Pro vs DeepSeek V4.1 Flash (1017)
Kimi K3.1 Pro scores higher on the Models at Work leaderboard (86 vs 80 out of 100). DeepSeek V4.1 Flash (1017) is about 7.6× cheaper per blended million tokens ($0.52 vs $4). On Artificial Analysis' independent Intelligence Index, Kimi K3.1 Pro leads 55 to 45.
| Kimi K3.1 Pro · Moonshot | DeepSeek V4.1 Flash (1017) · DeepSeek | |
|---|---|---|
| Leaderboard rank | #2 | #10 |
| Score (0–100) | 86 | 80 |
| Tier | Open weights | Fast and cheap |
| Price per 1M tokens | $2 in · $10 out | $0.30 in · $1.20 out |
| Context window | 1M | 1M |
| Open weights | Yes | Yes |
| Artificial Analysis Intelligence Index | 55 | 45 |
| Terminal-Bench 4.0 (vendor) | 65.7% | — |
| Best for | Agentic coding with an open-weight exit, 1M-token long-context work, Moving off Kimi K3 | Cheap coding tiers, Bulk generation, Experiments where data residency is not a 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 DeepSeek V4.1 Flash (1017) if…
- you need cheap coding tiers
- you need bulk generation
- you need experiments where data residency is not a constraint
Now measured: 45 on the Artificial Analysis index at 227 tokens/s and open weights, the fastest model near the top of the board.
Caveats: Weights are MIT-licensed on Hugging Face per DeepSeek; the 1017 snapshot's Terminal-Bench 4.0 figure is DeepSeek's own and is not counted. One independent index so far (Artificial Analysis 45, max setting); no Arena or Scale entry yet. Off-peak and peak pricing differ; the cheap numbers are off-peak. Read data-handling terms before enterprise use.
What practitioners say
Kimi K3.1 Pro: No practitioner threads recorded in Signals yet; left out of the score rather than guessed.
DeepSeek V4.1 Flash (1017): The 1,067-point HN thread on the earlier Flash release said the price is real and the coding gap to Opus is also real; nothing newer read this run, so sentiment is unscored.
Questions people ask
Which is better, Kimi K3.1 Pro or DeepSeek V4.1 Flash (1017)?
Kimi K3.1 Pro scores higher on the Models at Work leaderboard (86 vs 80 out of 100). DeepSeek V4.1 Flash (1017) is about 7.6× cheaper per blended million tokens ($0.52 vs $4). On Artificial Analysis' independent Intelligence Index, Kimi K3.1 Pro leads 55 to 45.
When should I choose Kimi K3.1 Pro over DeepSeek V4.1 Flash (1017)?
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 DeepSeek V4.1 Flash (1017) over Kimi K3.1 Pro?
Choose DeepSeek V4.1 Flash (1017) for cheap coding tiers, bulk generation, experiments where data residency is not a constraint. Now measured: 45 on the Artificial Analysis index at 227 tokens/s and open weights, the fastest model near the top of the board.
Which is cheaper, Kimi K3.1 Pro or DeepSeek V4.1 Flash (1017)?
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). DeepSeek V4.1 Flash (1017) costs $0.30 per million input tokens and $1.20 per million output tokens on DeepSeek's list price (DeepSeek 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.