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AI Model Comparison

Side-by-side spec sheet of frontier models: context window, input/output price, multimodal support, strengths, and best-fit use cases.

Updated June 2026
CompareModelContextMax outIn $/MOut $/MVisionToolsJSON
Gemini 1.5 Pro · Google2,000,0008,192$1.25$5
Gemini 1.5 Flash · Google1,000,0008,192$0.075$0.3
Claude Opus 4 · Anthropic200,0008,192$15$75
Claude Sonnet 4 · Anthropic200,0008,192$3$15
Claude Haiku 4 · Anthropic200,0008,192$0.8$4
o1 · OpenAI200,000100,000$15$60
GPT-4o · OpenAI128,00016,384$2.5$10
GPT-4o mini · OpenAI128,00016,384$0.15$0.6
Llama 3.1 70B · Meta128,0004,096$0.35$0.4
Llama 3.1 405B · Meta128,0004,096$2.7$2.7
Mistral Large 2 · Mistral128,0004,096$2$6
DeepSeek V3 · DeepSeek64,0008,192$0.27$1.1
Head-to-head notes
Claude Sonnet 4
Anthropic · 2025
Strengths: Excellent quality-to-price ratio. Default pick for production coding agents.
Watch out: Loses to Opus on deep reasoning and creative nuance.
GPT-4o
OpenAI · 2024
Strengths: Solid all-rounder with fast voice and image capabilities. Huge ecosystem of tooling.
Watch out: Reasoning behind Claude Opus / o1. Writing feels more generic.
Gemini 1.5 Pro
Google · 2024
Strengths: 2M-token context window — unmatched for feeding entire codebases or long videos.
Watch out: Quality dips at very long contexts. Safety filters can be intrusive.

Prices are list rates per million tokens as of publication. Always verify with the provider before budgeting.

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What it does

Side-by-side spec sheet of frontier models — context window, price, multimodal support, strengths, weaknesses — so you can pick the right one.

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How to use it

  1. Filter by vendor and sort by the metric that matters.
  2. Tick models to compare head-to-head.
  3. Read the strengths/watch-out notes.

Frequently asked questions

Which frontier model is best?
Depends on task. GPT-4o is well-rounded and cheap. Claude Opus 4 excels at writing, code, and structured output. Gemini 2.5 Pro has the largest context (2M) and strong multimodal. There's no single winner — benchmark on your specific task before committing.
How often do these specs change?
Models update every 3-6 months. Prices change more often (2024 saw 50%+ cuts across all providers). Context windows grow. Always check the vendor's pricing page for current numbers — this table is a point-in-time reference.
Should I use a smaller model for cost savings?
Often yes. GPT-4o mini is ~15x cheaper than GPT-4o and handles most production tasks. Claude Haiku is similarly much cheaper than Opus. Many workflows benefit from a 'small-fast model' routing tier plus premium model only for hard cases.
Is open-source competitive with closed models?
Closing the gap. Llama 3.1 405B matches GPT-4-class performance. DeepSeek R1 is competitive with o1 on reasoning at a fraction of the cost. For most tasks, top open-source runs on Together/Replicate/Groq at 50-80% less than closed APIs. Enterprise privacy use-cases benefit most from self-hosting.

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