Kimi K3.1 Pro vs Gemini 4 Argon
Kimi K3.1 Pro and Gemini 4 Argon are within three points on the Models at Work leaderboard, which we treat as a tie (86 vs 85). Gemini 4 Argon is about 2.0× cheaper per blended million tokens ($1.99 vs $4, one figure an Artificial Analysis estimate). On Artificial Analysis' independent Intelligence Index, Kimi K3.1 Pro leads 55 to 53.
| Kimi K3.1 Pro · Moonshot | Gemini 4 Argon · Google | |
|---|---|---|
| Leaderboard rank | #2 | #4 |
| Score (0–100) | 86 | 85 |
| Tier | Open weights | Frontier |
| Price per 1M tokens | $2 in · $10 out | $1.99 blended (estimate) |
| Context window | 1M | 1M |
| Open weights | Yes | No |
| Artificial Analysis Intelligence Index | 55 | 53 |
| Terminal-Bench 4.0 (vendor) | 65.7% | — |
| Arena text score | — | 1525 |
| Best for | Agentic coding with an open-weight exit, 1M-token long-context work, Moving off Kimi K3 | Chat and assistant products, Google Cloud shops, Price-sensitive frontier work |
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 Gemini 4 Argon if…
- you need chat and assistant products
- you need google cloud shops
- you need price-sensitive frontier work
Wins the popularity contest: first on Arena, mid-pack on the index, and priced like a workhorse.
Caveats: Google's public pricing page did not list Argon when read; the blended figure is Artificial Analysis' estimate.
What practitioners say
Kimi K3.1 Pro: No practitioner threads recorded in Signals yet; left out of the score rather than guessed.
Gemini 4 Argon: The announcement thread ran to 1,190 comments; the independent analysis thread was smaller and more measured.
Questions people ask
Which is better, Kimi K3.1 Pro or Gemini 4 Argon?
Kimi K3.1 Pro and Gemini 4 Argon are within three points on the Models at Work leaderboard, which we treat as a tie (86 vs 85). Gemini 4 Argon is about 2.0× cheaper per blended million tokens ($1.99 vs $4, one figure an Artificial Analysis estimate). On Artificial Analysis' independent Intelligence Index, Kimi K3.1 Pro leads 55 to 53.
When should I choose Kimi K3.1 Pro over Gemini 4 Argon?
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 Gemini 4 Argon over Kimi K3.1 Pro?
Choose Gemini 4 Argon for chat and assistant products, google cloud shops, price-sensitive frontier work. Wins the popularity contest: first on Arena, mid-pack on the index, and priced like a workhorse.
Which is cheaper, Kimi K3.1 Pro or Gemini 4 Argon?
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). Google does not publish a simple list price for Gemini 4 Argon; Artificial Analysis estimates a blended $1.99 per million tokens (three input to one output).
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.