Head-to-head
Claude Haiku 4.5 vs Gemini 3 Pro: which AI model wins in 2026?
Claude Haiku 4.5 ($5/1M out) and Gemini 3 Pro ($12/1M out (prompts ≤200K)) are two of the most-used AI models in 2026. Across 5 community votes, Claude Haiku 4.5 leads with 67% approval.
Quick verdict
On Reasoning, pick Gemini 3 Pro: the arena rates it 4.5/5 against 3/5 for Claude Haiku 4.5. On budget, Claude Haiku 4.5 wins: it starts at $5/1M out versus $12/1M out (prompts ≤200K) for Gemini 3 Pro.
Line-by-line comparison
Strengths and weaknesses
Claude Haiku 4.5
- 73.3% on SWE-bench Verified, about 90% of Sonnet 4.5's agentic coding at one third of the price
- Fast: more than 2x Sonnet 4 speed per Anthropic, with launch customers reporting 4-5x faster than Sonnet 4.5; ~92-110 output tok/s measured by Artificial Analysis
- Devs report precise, localized code edits that avoid touching irrelevant code, better than GPT-5 mini class in early testing
- Supports both vision input and extended thinking, rare at this price tier at launch
- Well suited as worker model in multi-agent setups (Sonnet/Opus plans, parallel Haiku sub-agents execute)
- Prompt caching reads at $0.10/1M and 50% Batch API discount cut effective cost further
- $5/1M output is pricey for a small model: Gemini Flash and GPT mini tiers undercut it several-fold on output-heavy tasks
- 200K context (vs 1M for Sonnet 5/Opus siblings) and 64K max output limit large-codebase and long-output work
- Mediocre cross-domain reasoning: users report weak results on GPQA, MedQA, MMMU style knowledge tasks
- Throughput varies widely in practice (82-208 tok/s reported) and quality degrades on long 7-8+ minute agentic sessions
- Knowledge cutoff (reliable to Feb 2025) is dated by mid-2026 standards
Gemini 3 Pro
- Topped LMArena at launch with a record 1501 Elo and scored 91.9% on GPQA Diamond, state of the art at release
- ARC-AGI-2 at 31.1%, roughly 6x Gemini 2.5 Pro (4.9%) and nearly double GPT-5.1 (17.6%) at the time
- Best-in-class multimodal understanding: 81% MMMU-Pro, 87.6% Video-MMMU, with a 1M-token context window
- Strong agentic coding: 76.2% SWE-bench Verified, 54.2% Terminal-Bench 2.0, 1487 Elo on WebDev Arena
- Undercut rivals on price at $2/$12 per 1M tokens, below Claude Sonnet-class pricing ($3/$15)
- Configurable thinking_level (low/medium/high) lets developers trade reasoning depth against latency and cost
- Overconfident hallucinations: on AA-Omniscience it gave a wrong answer 88% of the time instead of declining, vs 48% for Claude Sonnet 4.5 (the-decoder)
- Sycophancy widely reported by reviewers (Zvi Mowshowitz: 'vast intelligence with no spine'); needs tight system prompts
- Tool-calling reliability issues in agent stacks: devs reported tool outputs dumped into the chat thread and more scaffolding needed than OpenAI/Anthropic models
- Slow at high thinking level: time to first token measured around 30-60s on AI Studio despite ~130 tok/s output speed
- Retired: shut down on the Gemini API and AI Studio on March 9, 2026, with gemini-3-pro-preview now aliased to Gemini 3.1 Pro
Cast your verdict
One recommendation per tool per gladiator. It reshapes the crowd score everyone sees.
The arena’s verdict on Claude Haiku 4.5
Pick Haiku 4.5 if you are on the Anthropic stack and need near-Sonnet coding quality at low latency and a third of the price: it is a massive step up from Haiku 3.5 and excels as the worker model in multi-agent pipelines. It remains Anthropic's current small model as of July 2026, so it is the default cheap tier for Claude-based products. Avoid it for deep cross-domain reasoning, very large codebases (200K context cap), or pure cost-per-token shopping, where Gemini Flash and GPT mini tiers are now cheaper, and step up to Sonnet 5 when quality matters more than speed.
The arena’s verdict on Gemini 3 Pro
A landmark release that put Google back on top in late 2025, with a huge reasoning jump over Gemini 2.5 Pro and the best multimodal scores of its generation. As of mid-2026 there is no reason to choose it: Google shut it down on the API on March 9, 2026, and Gemini 3.1 Pro costs exactly the same while more than doubling ARC-AGI-2 performance (77.1% vs 31.1%). Teams on legacy deployments should migrate to 3.1 Pro, which the old model ID now points to anyway. Avoid it for hallucination-sensitive workloads unless you add grounding, a weakness reviewers flagged repeatedly.
What the crowd says
On Claude Haiku 4.5
“The precise localized edits are the underrated feature. It fixes the line that needs fixing and leaves the rest alone. GPT mini class models keep rewriting half my file.”
“Haiku 4.5 gives me about 90% of Sonnet agentic coding at a third of the price, and it is fast enough that edit loops feel instant. My default for quick fixes now.”
On Gemini 3 Pro
“Confidently wrong is its worst mode. On AA-Omniscience it gave a wrong answer 88% of the time instead of declining. Add the sycophancy and you need a tight system prompt to trust it.”
“ARC-AGI-2 at 31% was about 6x Gemini 2.5 Pro and nearly double GPT-5.1 at the time. For visual-heavy work (81 MMMU-Pro) nothing else came close.”
“1501 Elo on LMArena at launch was deserved. Multimodal is where it kills, I feed it lecture videos and dense PDFs and it just gets it. 1M context helps.”
Keep comparing
Frequently asked questions
Is Claude Haiku 4.5 better than Gemini 3 Pro?
The crowd currently sides with Claude Haiku 4.5: 67% recommend it, versus 57% for Gemini 3 Pro (5 votes). On Reasoning, Gemini 3 Pro rates higher (4.5/5 vs 3/5). The right pick depends on your use case. The line-by-line comparison on this page breaks down pricing, key specs and arena ratings.
Which is cheaper, Claude Haiku 4.5 or Gemini 3 Pro?
Claude Haiku 4.5 is cheaper: it starts at $5/1M out, while Gemini 3 Pro starts at $12/1M out (prompts ≤200K).
How much do Claude Haiku 4.5 and Gemini 3 Pro cost per 1M tokens?
Claude Haiku 4.5: $1/1M in per 1M input tokens, $5/1M out per 1M output tokens. Gemini 3 Pro: $2/1M in (prompts ≤200K) per 1M input tokens, $12/1M out (prompts ≤200K) per 1M output tokens.