Tech Comparisons
GPT-5.5 vs Claude Sonnet vs Gemini 3.1 Pro
Choosing the right AI model for your app affects cost, latency, and quality. We compare the three leading API models developers build on in mid-2026.
| Feature | GPT-5.5 | Claude Sonnet | Gemini 3.1 Pro |
|---|---|---|---|
| Model Version | GPT-5.5 (released Apr 23, 2026) — most token-efficient OpenAI model. | Claude Sonnet 4.6 — current default Anthropic model for production. | Gemini 3.1 Pro (released Mar 3, 2026) — best Google API model. |
| Input Price (per 1M tokens) | GPT-5.5: higher than GPT-5.4 (exact rate TBC by OpenAI). | Claude Sonnet 4.6: $3.00 / 1M input tokens. | Gemini 3.1 Pro: $2.00 / 1M input tokens (≤200K). |
| Output Price (per 1M tokens) | GPT-5.5: higher than predecessors (exact rate TBC). | Claude Sonnet 4.6: $15.00 / 1M output tokens. | Gemini 3.1 Pro: $12.00 / 1M output tokens. |
| Context Window | GPT-5.5: not yet officially confirmed. | 200K tokens. | 2M tokens — largest context of the three. |
| Speed (Latency) | Fast — matches GPT-5.4 per-token latency per OpenAI. | Fast — consistent latency on standard tasks. | Moderate — slightly higher latency on long context. |
| Prompt Caching | Yes — automatic caching, 50% discount on cached tokens. | Yes — explicit cache control, 90% discount on cached tokens. | Yes — automatic caching in AI Studio and API. |
| Function Calling / Tools | Excellent — parallel tool calls, structured outputs (JSON mode). | Excellent — tool use with extended thinking for agentic tasks. | Very good — function calling supported, strong tool use. |
| Vision / Multimodal | Full vision — images, PDFs, audio, computer use. | Full vision — images and documents. | Full vision + video understanding + 2M context. |
| Best For | Agentic coding, computer use, broad OpenAI-compatible integrations. | Long document pipelines, coding agents, high-quality output. | Long-context apps, video input, Google Cloud ecosystem. |
GPT-5.5 Pros & Cons
Pros
- Most capable OpenAI model — best agentic coding and computer use
- OpenAI-compatible API — works with every AI framework
- More token-efficient than GPT-5.4 at similar latency
- DALL-E and TTS available in same API
Cons
- Pricing higher than previous models — exact rates not yet published
- Context window not officially confirmed
- Rate limits strict on lower tiers
Claude Sonnet Pros & Cons
Pros
- Best output quality for writing and code
- 200K context — handle entire repos or legal docs
- Extended thinking available for complex reasoning
- Best prompt caching discount (90%) for repeated system prompts
Cons
- Most expensive output pricing of the three ($15/M)
- No OpenAI-compatible endpoint (different SDK)
- No video understanding
Verdict
GPT-5.5 is the most capable OpenAI model and best for agentic coding and computer use workflows. Claude Sonnet 4.6 wins on output quality and prompt caching economics — best for writing, coding agents, and long documents. Gemini 3.1 Pro offers the best value per token with a 2M context window — ideal for long-context apps, video processing, or Google Cloud deployments. Run a token cost estimate against your actual prompt sizes before committing.