Kimi K2.6vsGPT-4 Turbo
Kimi K2.6 | GPT-4 Turbo | |
|---|---|---|
| Specifications | ||
ParametersA rough measure of how big the model is. More parameters usually means more capable and more expensive to run, though it is a poor guide on its own — a smaller, newer model often beats a larger, older one. | 1T | — |
Context windowHow much text the model can hold in mind at once — your question, any documents you attach, the conversation so far, and its own reply. Go past it and the earliest part falls out of view. | 256k | 128k |
| API pricingUSD per 1M tokens · lower wins | ||
Input priceWhat you pay for everything you send the model — your question, plus any documents or earlier conversation you include with it. | $0.95 | $10.00 |
Output priceWhat you pay for the text the model writes back. It is normally the dearer half: producing an answer costs more than reading one. | $4.00 | $30.00 |
Cached input priceA reduced rate for text you send over and over. If every request starts with the same instructions or the same document, the provider keeps a copy ready and charges less to read it again. | $0.16 | — |
Cheapest inputLowest input rate across third-party providers, excluding the lab itself. The cheapest endpoint may run a quantised build or a shorter context — see "Available from" on the model page. | $0.57Inceptron | — |
Cheapest outputLowest output rate across third-party providers, excluding the lab itself. May come from a different provider than the cheapest input. | $2.4696Decart | — |
| Benchmarks | ||
GPQA DiamondScience — Graduate-level science questions in biology, physics, and chemistry — hard enough that subject-matter PhDs score around 65%. Higher is better. | 90.5% | 42.5% |
| BenchmarksPublished by one model only | ||
BullshitBench v2Nonsense detection — Given a confidently-worded but nonsensical prompt, does the AI spot that it makes no sense and push back — instead of playing along and inventing an answer? The score is how often it clearly called out the nonsense. Higher is better. | 65% | — |
SWE-Bench VerifiedCoding — Real coding tasks pulled from open-source projects — the AI has to find and fix actual bugs. A human-checked version of the original SWE-Bench. Higher is better. | 80.2% | — |
CursorBench v3.1Agentic coding — Cursor's own test of harder, real-world coding tasks inside a code editor. Higher is better. | 47.6% | — |
Next.js EvalsNext.js coding — Vercel's open eval of how well AI coding agents build and migrate real Next.js apps — measured as the share of tasks the agent completes successfully. Higher is better. | 67% | — |
LiveCodeBenchCompetitive coding — Coding problems published so recently the AI can't have seen them in training — a contamination-free test of raw programming skill. Higher is better. | 89.6% | — |
Arena Elo (Text)Community preference — Real people chat with two anonymous AIs side by side and vote for the answer they prefer. Votes become a chess-style Elo rating on arena.ai — it measures which AI people actually like, not test scores. Higher is better. | 1461 | — |
Arena Elo (Code)Community preference (code) — Like the text arena, but people vote on which AI writes better code. The votes become a chess-style Elo rating on arena.ai. Higher is better. | 1513 | — |
| Overview | ||
| Company | Moonshot AI | OpenAI |
| Release date | Apr 21 2026 | Nov 6 2023 |
| Access | Open Weight | Proprietary |
Other comparisons
Frequently asked questions
Kimi K2.6 leads GPT-4 Turbo on 1 of the 1 benchmark they both report (GPQA Diamond). Kimi K2.6 is cheaper on both input and output: $0.95 vs $10.00 per million input tokens, and $4.00 vs $30.00 per million output tokens. GPT-4 Turbo shipped 897 days before Kimi K2.6, so benchmark comparisons should account for the intervening progress.
Context windows are 256k (Kimi K2.6) vs 128k (GPT-4 Turbo). Kimi K2.6 is open weight, while GPT-4 Turbo is proprietary.
On GPQA Diamond, Kimi K2.6 leads at 90.5% vs GPT-4 Turbo at 42.5%.
Kimi K2.6 was released by Moonshot AI on Apr 21 2026.
GPT-4 Turbo was released by OpenAI on Nov 6 2023.
Kimi K2.6 leads on GPQA Diamond — Kimi K2.6 90.5% vs GPT-4 Turbo 42.5%.
Kimi K2.6 is cheaper on both input and output: $0.95 vs $10.00 per million input tokens, and $4.00 vs $30.00 per million output tokens. Rates are pay-as-you-go API prices verified on August 18, 2026.
Kimi K2.6 has a 256k context window; GPT-4 Turbo has 128k.
Kimi K2.6 is an open weight model released by Moonshot AI. GPT-4 Turbo is a proprietary model released by OpenAI.