GPT-6.1 Terra leads on coding; Kimi K3.1 Pro leads on tool use; reasoning is a statistical tie; GPT-6.1 Terra is cheaper per million tokens.
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As of 26 Oct 2026, 19:25 UTC · 24-hour board
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Both models on the same four boards, the same list-price view and the same drift detectors. Scores carry their standard error; a place is shared, written joint, when the gap is inside that noise.
| Measure | GPT-6.1 Terra | Kimi K3.1 Pro |
|---|---|---|
| Combinedscore ± standard error · place, 24-hour board | 90 ± 0.9joint 14th of 25 | 90 ± 0.5joint 14th of 25 |
| Codingscore ± standard error · place, 24-hour board | 91 ± 0.3joint 11th of 25 | 86 ± 1.0joint 20th of 25 |
| Reasoningscore ± standard error · place, 24-hour board | 95 ± 3.0joint 1st of 25 | 100 ± 0.3joint 1st of 25 |
| Tool usescore ± standard error · place, 24-hour board | 83 ± 1.5joint 16th of 25 | 87 ± 0.4joint 1st of 25 |
| List price per 1M tokensinput / output · blended 40/60 | $1 / $5$3.40 blended | $2 / $10$6.80 blended |
| Median response timecoding tasks, last 30 days | 10 s | 12 s |
| Pass ratecoding attempts, last 30 days | 75% | 70% |
| Cost per 1,000 correct answerscoding, last 30 days, every attempt billed | $3.99 | $9.10 |
| Drift statustrend on the 24-hour board · Page-Hinkley per suite | Holding steady | Holding steady |
| Tracked since | 13 Oct 2026 | 26 Oct 2026 |
The boards re-rank after every run, so the figures here follow the leaderboard: each model’s own page, GPT-6.1 Terra and Kimi K3.1 Pro, carry the full history. The whole board for each category is on best LLM for coding, best LLM for reasoning and best AI model for agents.
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The Coding board: seven repository debugging tasks graded by running the project’s own tests, including hidden tests the model never sees, re-tested every four hours.
GPT-6.1 Terra scores 91 ± 0.3 — joint 11th of the 25 models on the Coding board in the last 24 hours. Kimi K3.1 Pro scores 86 ± 1.0 — joint 20th of the 25 models on the Coding board in the last 24 hours. The gap of 5 points is beyond the measurement noise, so GPT-6.1 Terra leads on coding.
Over the last 30 days, GPT-6.1 Terra passed 75% of its coding attempts and Kimi K3.1 Pro 70%.
See every model on the Coding board on best LLM for coding, or each model’s own page, GPT-6.1 Terra and Kimi K3.1 Pro.
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The Reasoning board: four long, multi-turn working sessions every day, with continuity checked by running code against rules stated earlier in the session.
GPT-6.1 Terra scores 95 ± 3.0 — joint 1st of the 25 models on the Reasoning board in the last 24 hours. Kimi K3.1 Pro scores 100 ± 0.3 — joint 1st of the 25 models on the Reasoning board in the last 24 hours. The gap of 5 points is within the measurement noise, so the two are a statistical tie on reasoning.
See every model on the Reasoning board on best LLM for reasoning.
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The Tool use board: nine tasks, each in a real sandboxed machine — either the job is done at the end or it is not. Task completion, tool selection, parameter accuracy, efficiency, error handling, context awareness and safety are scored.
GPT-6.1 Terra scores 83 ± 1.5 — joint 16th of the 25 models on the Tool use board in the last 24 hours. Kimi K3.1 Pro scores 87 ± 0.4 — joint 1st of the 25 models on the Tool use board in the last 24 hours. The gap of 4 points is beyond the measurement noise, so Kimi K3.1 Pro leads on tool use.
See every model on the Tool use board on best AI model for agents.
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List prices are each provider’s standard rate per million tokens, cache-miss input and output. Cost per correct answer counts every attempt on the coding tasks, failed ones included, over the last 30 days.
GPT-6.1 Terra lists at $1 in / $5 out per 1M tokens; Kimi K3.1 Pro at $2 in / $10 out.
On a 40/60 input–output blend, Kimi K3.1 Pro costs about 2× as much per token as GPT-6.1 Terra.
Over the last 30 days, 1,000 correct coding answers cost about $3.99 with GPT-6.1 Terra and $9.10 with Kimi K3.1 Pro, every attempt billed, failed ones included.
The cheapest model that still passes the tests is on best value AI model.
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Median response time of one attempt or one session, from the same runs as the scores, over the last 30 days.
Median response time on the coding tasks over the last 30 days: GPT-6.1 Terra 10 s, Kimi K3.1 Pro 12 s.
The two are close.
On the reasoning sessions 1.5 min against 2.2 min and on the tool-use sessions 2.0 min against 2.2 min (GPT-6.1 Terra first).
Every model’s median is on fastest AI model.
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Page-Hinkley change-point detection (a CUSUM-family test) runs per suite on each model’s daily median, with every constant published; a real shift is confirmed over days, not hours. An hourly canary of two fixed coding probes catches sharp drops.
GPT-6.1 Terra is holding steady on the 24-hour board.
Kimi K3.1 Pro is holding steady on the 24-hour board.
The family pages answer the question for every model of a provider: Is ChatGPT getting worse? and Are AI models getting worse?. The method is on AI drift detection.
Three models free · email when a watched model's coding score falls five points in a week
Three models free · email when a watched model's coding score falls five points in a week
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Only a difference that clears a threshold counts: a board lead beyond the measurement noise (the leaderboard’s own tie rule), 10% on list price, 20% on response time or cost per correct answer.
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One OpenAI-compatible endpoint sends each request to whichever model the boards favour for that kind of work, with your own provider keys.
Yes. The Smart Router is one OpenAI-compatible endpoint with 14 auto-* routing modes: a quality mode such as auto-coding sends each request to the model placing highest on that board, the value modes pick within 5 points of the best and then the cheapest measured cost per run, and auto-split sends traffic by weights you set. Routing is drift-aware by default, uses your own provider keys and adds zero markup on tokens. Free includes 1,000 routed requests a month.
Every mode is described in the router documentation.
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Every model on the board runs the same tasks on the same schedule: coding every four hours, reasoning and tool use daily, with an hourly canary probe.
Scores come from our own runs through each provider’s public API, not vendor-reported numbers. Every model gets the same prompts and output budget, and the same sampling settings wherever a provider accepts them, and is graded by executing what it produces. Every score carries a standard error from its own run-to-run repeatability; models whose lead is inside that noise share a place, written joint.
The methodology is public — every weight, statistical test and drift constant. The test tasks are private, so no lab can train on them. The full method, weights and constants are on the methodology page.
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GPT-6.1 Terra scores 91 ± 0.3 — joint 11th of the 25 models on the Coding board in the last 24 hours. Kimi K3.1 Pro scores 86 ± 1.0 — joint 20th of the 25 models on the Coding board in the last 24 hours. The gap of 5 points is beyond the measurement noise, so GPT-6.1 Terra leads on coding. Over the last 30 days, GPT-6.1 Terra passed 75% of its coding attempts and Kimi K3.1 Pro 70%.
GPT-6.1 Terra scores 95 ± 3.0 — joint 1st of the 25 models on the Reasoning board in the last 24 hours. Kimi K3.1 Pro scores 100 ± 0.3 — joint 1st of the 25 models on the Reasoning board in the last 24 hours. The gap of 5 points is within the measurement noise, so the two are a statistical tie on reasoning.
GPT-6.1 Terra scores 83 ± 1.5 — joint 16th of the 25 models on the Tool use board in the last 24 hours. Kimi K3.1 Pro scores 87 ± 0.4 — joint 1st of the 25 models on the Tool use board in the last 24 hours. The gap of 4 points is beyond the measurement noise, so Kimi K3.1 Pro leads on tool use.
GPT-6.1 Terra lists at $1 in / $5 out per 1M tokens; Kimi K3.1 Pro at $2 in / $10 out. On a 40/60 input–output blend, Kimi K3.1 Pro costs about 2× as much per token as GPT-6.1 Terra. Over the last 30 days, 1,000 correct coding answers cost about $3.99 with GPT-6.1 Terra and $9.10 with Kimi K3.1 Pro, every attempt billed, failed ones included.
Median response time on the coding tasks over the last 30 days: GPT-6.1 Terra 10 s, Kimi K3.1 Pro 12 s. The two are close. On the reasoning sessions 1.5 min against 2.2 min and on the tool-use sessions 2.0 min against 2.2 min (GPT-6.1 Terra first).
GPT-6.1 Terra is holding steady on the 24-hour board. Kimi K3.1 Pro is holding steady on the 24-hour board. Page-Hinkley change-point detection (a CUSUM-family test) runs per suite on each model’s daily median, with every constant published; a real shift is confirmed over days, not hours. An hourly canary of two fixed coding probes catches sharp drops.
GPT-6.1 Terra leads on coding; Kimi K3.1 Pro leads on tool use; reasoning is a statistical tie; GPT-6.1 Terra is cheaper per million tokens. Choose GPT-6.1 Terra when the work is coding: it leads the Coding board by 5 points in the last 24 hours (91 ± 0.3 against 86 ± 1.0); price per token matters: it lists at $1 in / $5 out per 1M tokens against $2 in / $10 out; cost per correct answer matters: about $3.99 per 1,000 correct coding answers against $9.10 over the last 30 days. Choose Kimi K3.1 Pro when the work is tool use: it leads the Tool use board by 4 points in the last 24 hours (87 ± 0.4 against 83 ± 1.5).
Yes. The Smart Router is one OpenAI-compatible endpoint with 14 auto-* routing modes: a quality mode such as auto-coding sends each request to the model placing highest on that board, the value modes pick within 5 points of the best and then the cheapest measured cost per run, and auto-split sends traffic by weights you set. Routing is drift-aware by default, uses your own provider keys and adds zero markup on tokens. Free includes 1,000 routed requests a month.
The Smart Router sends each request to whichever of GPT-6.1 Terra and Kimi K3.1 Pro — or any model on the board — the boards favour for that kind of work, with your own provider keys and zero markup on tokens.
1,000 routed requests a month free · your own provider keys · no card
Free account · 24 hours, 7 days and 30 days · no card
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