AI chat comparison · 2026-09-30

AI chat comparison: same prompt, every model, side by side

What a usable AI chat comparison looks like

Most “AI chat comparison” pages hand you a ranking built from marketing claims or cherry-picked demos. A comparison is only usable when three things hold: every model gets the same prompt, the answers are read side by side, and the conclusion is tied to a task you actually have. This page keeps both halves of that standard: the latest public test data we track (dated and sourced below), and the method to run the same comparison on your own prompts in one click.

The comparison table: latest public test results

Below are the current public results for the models ModelAny can reach, grouped by test. Each table lists only the models with a public result in that exact test—models without one are omitted, and scores from different tests cannot be added up. Exact model versions and retrieval dates are shown so newer generations are not judged against older ones.

SWE-bench Verified · real software-issue fixing

SWE-bench Verified measures how often an AI coding setup can fix real GitHub issues. A higher resolved percentage means more issues were fixed in that specific test setup.

Retrieved: Sep 29, 2026, 2:44 PM · Open original leaderboard

ProductExact model versionRankScoreMetric
Claude Sonar Foundation Agent + Claude 4.5 Opus 1 79.2% Resolved (%)
Doubao TRAE + Doubao-Seed-Code 3 78.8% Resolved (%)
Gemini live-SWE-agent + Gemini 3 Pro Preview (2025-11-18) 4 77.4% Resolved (%)
ChatGPT JoyCode + Claude 4 Sonnet + GPT-4.1 17 74.6% Resolved (%)
GLM GLM 5 (high) 25 72.8% Resolved (%)
Kimi Lingxi v1.5 x Kimi K2 35 71.2% Resolved (%)
DeepSeek DeepSeek V3.2 (high) 46 70% Resolved (%)
Qwen Nebius AI Qwen 2.5 72B Generator + LLama 3.1 70B Critic 137 40.6% Resolved (%)

LiveBench · agentic coding

LiveBench scores models on regularly refreshed objective tasks. Higher category scores mean better measured performance on that task type—not a universal ranking.

Retrieved: Sep 29, 2026, 2:44 PM · Open original leaderboard

ProductExact model versionRankScoreMetric
DeepSeek deepseek-v4.1-flash-max 1 77.27266666666667 Category score (points)
Claude claude-opus-5-5-max-effort 2 71.717 Category score (points)
Kimi kimi-k3 11 62.17166666666666 Category score (points)
GLM glm-5.3 15 60.909 Category score (points)
Gemini gemini-3.7-flash-high 19 58.282999999999994 Category score (points)
ChatGPT gpt-6-astra-max 21 57.323 Category score (points)

LiveBench · coding tasks

LiveBench scores models on regularly refreshed objective tasks. Higher category scores mean better measured performance on that task type—not a universal ranking.

Retrieved: Sep 29, 2026, 2:44 PM · Open original leaderboard

ProductExact model versionRankScoreMetric
Claude claude-sonnet-5-5-max-effort 1 91.366 Category score (points)
ChatGPT gpt-5.6-sol-max 7 83.941 Category score (points)
Kimi kimi-k3 15 81.4455 Category score (points)
DeepSeek deepseek-v4.1-flash-max 20 80.037 Category score (points)
GLM glm-5.2 22 79.654 Category score (points)
Gemini gemini-3.7-flash-high 27 78.8885 Category score (points)

LiveBench · data analysis

LiveBench scores models on regularly refreshed objective tasks. Higher category scores mean better measured performance on that task type—not a universal ranking.

Retrieved: Sep 29, 2026, 2:44 PM · Open original leaderboard

ProductExact model versionRankScoreMetric
ChatGPT gpt-6-astra-max 1 82.97333333333334 Category score (points)
Claude claude-fable-5-max-effort 4 80.53766666666667 Category score (points)
DeepSeek deepseek-v4-flash-vision-exp 11 79.47666666666667 Category score (points)
Kimi kimi-k3 19 78.73366666666668 Category score (points)
Gemini gemini-3.1-pro-preview-high 21 78.54133333333334 Category score (points)
GLM glm-5.3-flash 31 76.401 Category score (points)

LiveBench · instruction following

LiveBench scores models on regularly refreshed objective tasks. Higher category scores mean better measured performance on that task type—not a universal ranking.

Retrieved: Sep 29, 2026, 2:44 PM · Open original leaderboard

ProductExact model versionRankScoreMetric
Gemini gemini-3.8-flash-high 1 81.4125 Category score (points)
Claude claude-fable-5-max-effort 6 75.77074999999999 Category score (points)
ChatGPT gpt-6-astra-max 8 75.57900000000001 Category score (points)
Kimi kimi-k3 22 71.36275 Category score (points)
DeepSeek deepseek-v4-flash-vision-exp 24 70.95824999999999 Category score (points)
GLM glm-5.3 31 69.304 Category score (points)

LiveBench · language tasks

LiveBench scores models on regularly refreshed objective tasks. Higher category scores mean better measured performance on that task type—not a universal ranking.

Retrieved: Sep 29, 2026, 2:44 PM · Open original leaderboard

ProductExact model versionRankScoreMetric
Claude claude-fable-5-max-effort 1 90.68400000000001 Category score (points)
ChatGPT gpt-6-astra-max 3 89.43066666666668 Category score (points)
Gemini gemini-3.8-flash-high 5 87.79266666666666 Category score (points)
Kimi kimi-k3 9 85.528 Category score (points)
DeepSeek deepseek-v4-pro-0813 24 82.074 Category score (points)
GLM glm-5.3 29 79.85633333333332 Category score (points)

LiveBench · mathematics

LiveBench scores models on regularly refreshed objective tasks. Higher category scores mean better measured performance on that task type—not a universal ranking.

Retrieved: Sep 29, 2026, 2:44 PM · Open original leaderboard

ProductExact model versionRankScoreMetric
Claude claude-opus-5-5-max-effort 1 97.07749999999999 Category score (points)
ChatGPT gpt-6-astra-max 3 96.80624999999999 Category score (points)
DeepSeek deepseek-v4-pro-0813 14 95.08624999999999 Category score (points)
Gemini gemini-3.7-flash-high 18 93.46799999999999 Category score (points)
GLM glm-5.2 33 89.78125 Category score (points)
Kimi kimi-k3 51 84.43675 Category score (points)

LiveBench · reasoning

LiveBench scores models on regularly refreshed objective tasks. Higher category scores mean better measured performance on that task type—not a universal ranking.

Retrieved: Sep 29, 2026, 2:44 PM · Open original leaderboard

ProductExact model versionRankScoreMetric
ChatGPT gpt-6-astra-max 1 92.65375 Category score (points)
Claude claude-opus-5-5-max-effort 2 92.15375 Category score (points)
Kimi kimi-k3 7 90.673 Category score (points)
Gemini gemini-3.8-flash-high 16 89.29325 Category score (points)
DeepSeek deepseek-v4.1-flash-max 29 86.69225 Category score (points)
GLM glm-5.3 33 85.803 Category score (points)

Arena · coding preference

Arena asks people to pick the better answer without knowing which model wrote it. A higher Elo means more preference votes in that category—not an overall product ranking.

Retrieved: Sep 29, 2026, 2:44 PM · Open original leaderboard

ProductExact model versionRankScoreMetric
Claude claude-opus-5.5-max 1 1827 Elo (Elo)
ChatGPT gpt-6-astra-max 2 1792 Elo (Elo)
Kimi kimi-k3-max 9 1660 Elo (Elo)
DeepSeek deepseek-v4.1-flash-max 16 1621 Elo (Elo)
GLM glm-5.3-max 18 1619 Elo (Elo)
Gemini gemini-3.7-flash-high 23 1593 Elo (Elo)

Arena · search-style preference

Arena asks people to pick the better answer without knowing which model wrote it. A higher Elo means more preference votes in that category—not an overall product ranking.

Retrieved: Sep 29, 2026, 2:44 PM · Open original leaderboard

ProductExact model versionRankScoreMetric
ChatGPT gpt-5.6-sol-xhigh 1 1257 Elo (Elo)
Claude claude-opus-4-6-search 2 1253 Elo (Elo)
Wenxin ernie-5.1 6 1227 Elo (Elo)
Gemini gemini-3.1-pro-grounding 9 1210 Elo (Elo)

Arena · general chat preference

Arena asks people to pick the better answer without knowing which model wrote it. A higher Elo means more preference votes in that category—not an overall product ranking.

Retrieved: Sep 29, 2026, 2:44 PM · Open original leaderboard

ProductExact model versionRankScoreMetric
Claude claude-opus-5.5-high 1 1509 Elo (Elo)
Gemini gemini-3.8-flash-high 10 1492 Elo (Elo)
Kimi kimi-k3-max 16 1488 Elo (Elo)
ChatGPT gpt-5.6-sol-xhigh 19 1483 Elo (Elo)
GLM glm-5.3-max 24 1480 Elo (Elo)
DeepSeek deepseek-v4.1-flash-max 29 1477 Elo (Elo)

Prefer one test per model pair with methodology notes? Browse all public benchmark snapshots by scenario, or open a pair such as ChatGPT vs Claude, ChatGPT vs DeepSeek or ChatGPT vs Gemini.

Run the comparison on your own prompts: the five-step method

  1. Fix the task first. Pick a real task—fix this failing test, draft this reply, summarize this contract clause—and write down what a good answer must contain before you read any model.
  2. Freeze one prompt. Word it once and send the identical text everywhere. Retyped prompts drift, and drifted prompts measure your typing, not the models.
  3. Send to every model at once. In ModelAny, tick the models—ChatGPT, Claude, Gemini, DeepSeek, Grok, Tencent Yuanbao, Wenxin, Qwen, Doubao, Kimi, GLM—and send. Each official site answers under your own account.
  4. Score on four axes. Factual accuracy (verifiable claims), completeness against your criteria, edit cost (what you had to fix), and speed. Note who cited sources, who hedged, who invented.
  5. Re-run on a second task before deciding. One prompt makes a data point; two or three different task types make a pattern. Models lead in different categories—the tables above say the same thing.

The full walkthrough with a scoring rubric is in the side-by-side comparison method; the three-way version is in ChatGPT vs Claude vs Gemini on the same prompt.

One click instead of eleven tabs

Manual comparison means opening each site, pasting the prompt, and juggling tabs until context falls apart. ModelAny is a free Chrome and Edge extension that sends one prompt to up to 11 official AI sites—ChatGPT, Claude, Gemini, DeepSeek, Grok, Kimi, Qwen, Doubao, GLM, Tencent Yuanbao and Wenxiaoyan—and lines the answers up side by side. It uses the sessions you already have: no API key, no subscription, and no ModelAny server in the middle. Drafts, settings, and history stay in your browser.

New here? Start with how to ask multiple AI at once, or the same-prompt model comparison workflow.

Frequently asked questions

Which AI chat is best right now?

There is no single answer: the honest ranking changes by task and by model version. The public test tables on this page show measured results with dates and sources, and the same-prompt method shows you how to settle it for your own task in minutes.

How do I compare AI chatbots fairly?

Freeze one prompt, send the identical text to every model you care about, and score the answers against success criteria you wrote before reading them—accuracy, completeness, edit cost. Comparing answers to differently-worded prompts tells you about prompts, not models.

Which models can I compare with ModelAny?

Eleven official sites: ChatGPT, Claude, Gemini, DeepSeek, Grok, Kimi, Qwen, Doubao, GLM (ChatGLM), Tencent Yuanbao and Wenxiaoyan (ERNIE)—side by side, from one prompt box.

Is there a free AI chat comparison tool?

ModelAny is free with no subscription or credits: it sends one prompt to the official sites under the accounts you already have. The benchmark tables on this page are also free to read, with sources linked.

What does the comparison table on this page measure?

Public, third-party test results—Arena preference votes, SWE-bench Verified issue fixing, LiveBench task scores—shown per category with the exact model version, retrieval date and a link to the original leaderboard. They are measurements under stated conditions, not a universal ranking.

Run this comparison on your own prompts

Install ModelAny free on Chrome or Edge, ask once, and read answers from 11 AI sites side by side. Chrome Web Store · Microsoft Edge Add-ons

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