CorX Labs

Head to head

Claude Haiku 4.5 vs Gemini 2.5 Flash

Claude Haiku 4.5 from Anthropic against Gemini 2.5 Flash from Google DeepMind — specification, price and every benchmark both makers have published, in one table.

Benchmarks

Gemini 2.5 Flash leads

Gemini 2.5 Flash wins 2 of the 2 benchmarks both models report, Claude Haiku 4.5 wins 0, consistently. The average gap across shared tests is 3.1 points.

Price

Gemini 2.5 Flash is cheaper

On a 3:1 input-to-output mix, Gemini 2.5 Flash costs $0.85 per million tokens against $2.00 for Claude Haiku 4.5 — about 2.4× less. Remember that a reasoning model bills its thinking as output, so cost per answer can diverge much further than cost per token.

What actually differs

  • Gemini 2.5 Flash takes 1M tokens of context against 200K — 5.2× more room for long documents or a large codebase.

Scorecard

Which is better at what

Maths, coding, reasoning and the rest — one line each, averaged over the benchmarks both models actually report.

Which model scores higher in each capability category, averaged over the benchmarks all of them report.
CategoryClaude Haiku 4.5Gemini 2.5 FlashBetter at this
ReasoningGPQA Diamond73.0%78.3%Gemini 2.5 Flash+5.3
MathsAIME 202577.0%78.0%Gemini 2.5 Flash+1.0
CodingOnly one model reports thisNot comparable
KnowledgeNeither model reports thisNot comparable
MultimodalOnly one model reports thisNot comparable
Instruction followingNeither model reports thisNot comparable
Human preferenceOnly one model reports thisNot comparable
Categories wonOut of 2 comparable02Gemini 2.5 Flash

Each category averages only the benchmarks every model here reports, so no one is credited for a test the other did not run. A category with no shared test is marked Not comparable rather than guessed at.

Side by side

Claude Haiku 4.5 and Gemini 2.5 Flash, row by row

AttributeClaude Haiku 4.5AnthropicGemini 2.5 FlashGoogle DeepMind
Specification
MakerWho built itAnthropicGoogle DeepMind
Released2025-102025-04
Context windowHow much can go in at once200,000 tokens1,048,576 tokens
Max output64,000 tokens65,536 tokens
InputText, ImageText, Image, Audio, Video
ReasoningSpends extra tokens thinking before it answersYesYes
Tool callingYesYes
Knowledge cutoff2025-022025-01
LicenceProprietaryProprietary
Open weightsCan you download and run it yourselfNoNo
Price
Input priceUSD per million tokens in$1.00$0.30
Output priceUSD per million tokens out$5.00$2.50
Cached input$0.10$0.075
Blended 3:1A 3-in-to-1-out million-token mix — a fairer single number than input price alone$2.00$0.85Cheapest
Published benchmarks
GPQA Diamond198 graduate-level physics, chemistry and biology questions written to be Google-proof. PhD holders in the matching field score about 65%.73%78.3%Best
AIME 2025The American Invitational Mathematics Examination — 15 problems, integer answers, no partial credit. A standard test of multi-step maths reasoning.77%78%Best
SWE-bench Verified500 human-validated GitHub issues from real Python repositories. The model must produce a patch that makes the project's own tests pass.73.3%Not reported
MMMUCollege-level questions that require reading charts, diagrams, tables and photographs alongside the text.Not reported79.7%
LMArena EloElo rating from blind pairwise votes by the public on LMArena. Measures what people prefer, not what is correct.Not reported1393
LinksFull pageFull page
Row verified2026-082026-08

Where these numbers come from

Every score on this page is a published figure, taken from the model's own card, system card, technical report or release post, or from a public leaderboard. CorX Labs did not run these evaluations. Most are self-reported by the lab that built the model, which means they were produced under that lab's own choice of prompt, scaffold and number of attempts — so treat them as a starting point for a shortlist, not as a settled ranking.

A score someone other than the model's maker measured is marked Independent and names its measurer. Those are the stronger numbers on this page — an outside harness has no reason to flatter anyone — and there are not many of them.

Where a figure has not been published, the cell reads Not reported rather than an estimate. Nothing here is inferred, interpolated or guessed. Each model records the month its row was last checked. Full method and caveats.

Questions

Claude Haiku 4.5 or Gemini 2.5 Flash?

Is Claude Haiku 4.5 better than Gemini 2.5 Flash?

Gemini 2.5 Flash wins 2 of the 2 benchmarks both models report, Claude Haiku 4.5 wins 0, consistently. The average gap across shared tests is 3.1 points.

Which is cheaper, Claude Haiku 4.5 or Gemini 2.5 Flash?

On a 3:1 input-to-output mix, Gemini 2.5 Flash costs $0.85 per million tokens against $2.00 for Claude Haiku 4.5 — about 2.4× less. Remember that a reasoning model bills its thinking as output, so cost per answer can diverge much further than cost per token.

What is the difference between Claude Haiku 4.5 and Gemini 2.5 Flash?

Gemini 2.5 Flash takes 1M tokens of context against 200K — 5.2× more room for long documents or a large codebase.