Head-to-head breakdowns of the AI models and tools that matter — on benchmarks, capabilities and price.
26 comparisons · benchmark figures anchored to the Artificial Analysis index v4.3.2, captured September 30, 2026 · newest comparison October 15, 2026
Google’s Gemini 4 Argon takes on the three build briefs Claude Opus 5.5, GPT-6 Astra and Grok 4.7 have already answered. A motorway interchange, a seaside fairground and a cinematic rocket launch, one attempt each at the highest reasoning setting on offer, with no way to look at what it built. All twelve builds run below, untouched, so you can judge them yourself.
Read comparison →Claude Haiku 5.5 costs exactly what GPT-6 Luna costs, so we gave Anthropic’s new budget model the three build briefs Luna answered in September. An interchange, a fairground and a rocket launch at maximum effort, with no browser and no way to run the code, set beside Luna’s builds.
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Three AI models got one prompt to rebuild the signature moment of No Man’s Sky: fly down from orbit, land by hand on a planet, then step out and walk. Claude Opus 5.5, GPT-6 Astra and Grok 4.7 had one attempt each and had to test their own game before handing it in. All three are playable here.
Read comparison →GPT-6.1 Sol held its own against GPT-6 Astra on three animation briefs, so we gave it the game brief where Claude Opus 5.5 set the bar. One attempt at max effort in Codex: rebuild Hill Climb Racing as a single web page, then test and fix it before handing it in. Both games are here for you to drive.
Read comparison →OpenAI says GPT-6.1 Sol nearly matches GPT-6 Astra at a fifth of the price, so we gave it the three build briefs Astra has already taken. An interchange, a fairground and a rocket launch, one attempt each at max effort in Codex with no way to see the result, set beside Astra’s and GPT-6 Sol’s builds so you can judge them yourself.
Read comparison →Claude Sonnet 5.5 costs half as much as Opus 5.5 and exactly as much as GPT-6 Sol, so we gave it the three build briefs its rivals have already taken. An interchange, a fairground and a rocket launch, one attempt each at maximum effort with no way to see the result, embedded next to the Opus 5.5, GPT-6 Astra and Sol builds so you can judge them yourself.
Read comparison →After a poor Hill Climb result, is OpenAI’s GPT-6 Sol a step back from the GPT-5.6 Sol it replaces? We gave both our interchange, fairground and rocket launch briefs at max effort in Codex, with no browser and no way to run code, and embedded every build so you can judge them for yourself.
Read comparison →Claude Opus 5.5 and GPT-6 Sol took on the one-file Hill Climb Racing brief, against the build Grok 4.7 made for the second field. Opus 5.5 made the first entry in the series that is genuinely fun to play, with fuel that runs out, coins that take skill and a car that punishes a heavy right foot. It scored 19 out of 20, Grok 4.7 took 10 and GPT-6 Sol took 6. All three are playable in the article.
Read comparison →OpenAI's two cheaper GPT-6 models took on the three briefs GPT-6 Astra answered in September, and the flagship won every round. Astra finished with 10 points, Sol took 5 and Luna took 3, the same order as the price list. Sol and Luna built each brief two to six times faster, and every one of their six builds shipped a fault you can see.
Read comparison →Claude Opus 5.5 beat Fable 5.1 and GPT-6 Astra on the three briefs this series gives every frontier model: 10 points to Fable’s 9 and Astra’s 8. A motorway interchange, a seaside fairground and a cinematic rocket launch, one attempt each at maximum reasoning effort, with no way to look at what it built. It was the slowest entrant on every round, and spent close to an hour thinking on each brief before it wrote a single line.
Read comparison →The same one-file game brief from September, handed to three models that had never attempted it: one from Anthropic, one from OpenAI, one from xAI. All three passed every requirement the brief actually stated. All three then missed something it did not. Play all three builds in the article.
Read comparison →SpaceXAI’s Grok 4.7 took the three briefs this series has handed every frontier model — a motorway interchange, a seaside fairground and a cinematic rocket launch — against Claude Fable 5.1 and GPT-6 Astra. One attempt each, maximum reasoning effort, no looking at what they built. Every mechanism Grok was asked for is present and computed correctly. In all three, the thing a viewer actually watches was never connected to it.
Read comparison →Both models rebuilt the same racing game from one brief. One chose a muted desert, the other bright arcade colour. Both are playable here. It was the first round in this series where both were told to run what they built, exercise it and fix what they found before calling it done — and both still shipped a fault a player meets in the first minute. Fable 5.1 took it 15–14, the narrowest result this series has recorded.
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The same three build briefs, one attempt each, no browser — but handed to the middle of each lab’s range instead of the top. Anthropic’s Claude Sonnet 5 and OpenAI’s GPT-5.6 Terra both broke the same fairground ride in the same new way, and one of them shipped a game that never runs. All six builds are live in the article.
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Claude Opus 5 and GPT-5.6 Sol got the same three build briefs — a playable Pac-Man, an animated seaside fairground and a motorway interchange — one attempt each, with no browser to check their own work. All six builds run live in the article: play both games, watch the rest, and see which one holds up.
Read comparison →OpenAI’s GPT-6 Astra and Anthropic’s Claude Fable 5.1 got the same three build briefs — a motorway interchange, a seaside fairground and a cinematic rocket launch — one attempt each, at maximum reasoning effort, and neither could open a browser to check its own work. All six builds run live inside the article, faults and all: a bridge that hides a truck mid-crossing, a carousel that is not doing what it looks like it is doing, and two rockets with very different ideas of what a launch is. Score it yourself.
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We gave four Claude models — Fable 5.1, Opus 5, Fable 5 and Sonnet 5 — the same five build briefs at maximum reasoning effort, one attempt each, with no browser to check their work. All twenty builds run live inside the article. Fable 5.1 won four of the five rounds and finished only a single point clear, because the round it lost was the one where its code never ran at all.
Read comparison →Four agents, one decision. We score GitHub Copilot, Cursor, Claude Code and OpenAI Codex on quality (50%), price (30%) and speed (20%) — then show how the winner changes the moment you change the weights.
Read comparison →Z.ai’s new open-weight model scores 57.0 on the Artificial Analysis Intelligence Index — six points behind Claude Opus 5 and under two behind GPT-5.6 Sol, at $0.15 per million input tokens. It loses the flagship fight and wins the one that matters for volume: it beats Sonnet 5, Terra and Luna outright.
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We gave Claude Opus 5, Fable 5 and Sonnet 5 the same three build briefs — an animated SVG fairground, a falling-sand physics sandbox and a self-solving Rubik’s cube — one run each, no retries, no browser. All nine builds run live inside the article. Opus 5 takes it 8–6–3, and the biggest surprise is the clock: the largest model was the fastest on every round, by a factor of nearly three.
Read comparison →Artificial Analysis scored Grok 4.6 at 61 on its Intelligence Index — level with GPT-5.6 Sol at max, behind Fable 5 at 62 and Opus 5 at 63. It costs $2/$6 per million tokens against $5/$25 and $5/$30, and finishes long agentic tasks in ~53 turns where Opus 5 takes ~103. It also trails both rivals by eight points on the hardest software-engineering evals.
Read comparison →OpenAI split GPT-5.6 into Sol, Terra and Luna. Anthropic shipped one model with an effort dial. Put both on the same cost-independent index and the settings line up exactly — including one result that should change how you configure your API calls.
Read comparison →Opus 5 costs the same as the Opus 4.8 it replaces, beats the double-priced Fable 5 on Anthropic's own coding charts, and burns a fraction of the tokens doing it. We lined up every published number — specs, prices, benchmarks — and flagged exactly where the comparisons don't hold.
Read comparison →We pasted identical prompts into Claude Opus 4.8 and Claude Fable 5 — an animated highway interchange, a one-file Space Invaders, a pure-SVG aquarium, and a 3D rocket launch — one shot each, no retries. Everything runs live inside the article. Four builds in, it is dead level at 2–2 — and the launch round flips the very pattern the first three revealed.
Read comparison →A BitsMinds analysis. The frontier fight has moved from models to the agents wrapped around them. We line up the three coding agents developers actually argue about in 2026 — Anthropic’s terminal-native Claude Code, OpenAI’s everywhere-at-once Codex, and Google’s agent-first Antigravity IDE — across form factor, autonomy, verification, model choice and price. The short version: Claude Code owns deep terminal autonomy, Codex wins ubiquity, and Antigravity is the open, free, multi-agent cockpit. Here is the full scorecard.
Read comparison →A BitsMinds analysis. We put each lab’s strongest model through the benchmark portfolio that actually separates frontier systems in 2026 — GPQA Diamond, ARC-AGI-2, AIME, SWE-bench, BFCL and more — then weigh price, context and speed. The short version: Gemini 3.1 Ultra is the sharpest reasoner and the best value, Claude Opus 4.8 owns real coding and agentic work, and GPT-5.5 is the strong all-rounder that everyone already has. Here is the full scorecard.
Read comparison →Every comparison on this page is one of two kinds, and the kind changes how much weight a verdict can carry. A benchmark comparison lines models up on published numbers: the independent Artificial Analysis Intelligence Indexwhere every model is measured under one methodology, and each vendor's own system-card figures where it is not. Those pieces always say which index version and which model configuration — maximum effort, high, medium — a score belongs to, because a score without its configuration is not a fact. A hands-on comparison comes from BitsMinds Lab: the same build brief to every model, one attempt each, and every build embedded in the article so you can check our scoring against the evidence.
Three habits keep these pages honest, and they are worth adopting as a reader. First, never compare index scores across articles from different months. Artificial Analysis re-bases the index when its evaluation set changes — the current version is v4.3.2— and every model's number moves with it, so a 61 in a July piece and a 53 in September can describe the same model on the same day. Second, separate the product from the model: a ChatGPT Plus review is about a $20 plan, a GPT-6 Astra comparison is about an API model, and the two change on different schedules. Third, read price as cost per finished task, not per token. Our GPT-6 Astra review is the worked example: two models at an identical $10/$50 list price, with a 2.7× gap in what the same benchmark cost to complete, because one used a third of the tokens.
Benchmark figures are transcribed from the Artificial Analysis leaderboard on the capture date shown on our leaderboard (currently September 30, 2026, index v4.3.2), or from the vendor system card an article cites inline. Plan prices in the interactive compare toolcome from our tool database and the vendors' pricing pages, and each tool page shows when its facts were last re-checked. Hands-on results are single runs; the conditions of each — attempts, effort setting, what the model could and could not do — are stated on the article. If you want the practical follow-through after a comparison, the coding-tool buyer's guide turns the numbers into a decision, and our reviews cover the same models as products you can actually buy.
Benchmark comparisons use one independent yardstick where possible — the Artificial Analysis Intelligence Index — alongside each vendor's published system-card figures, always labelled with the index version and the model configuration measured. Hands-on comparisons come from BitsMinds Lab, where every model gets the same brief and one attempt, and every build is live in the article.
Artificial Analysis re-bases its Intelligence Index when it changes the evaluation set, and every model's number moves. An article quotes the version current when it was written, so compare scores within one article or on the leaderboard, never across articles from different months.
Not necessarily. Two models with the same price per million tokens can differ several-fold in what a finished task costs, because one burns far more tokens reaching its answer. Where a comparison quotes cost, it says whether that is list price per token or measured cost per task.
The articles are written analyses of specific match-ups with a dated verdict. The interactive compare tool puts two or three tools' plans, features and capability scores side by side from our tool database, for any combination you choose.