LLM ReferenceLLM Reference

Claude Sonnet 4.6 vs o3 Deep Research

Claude Sonnet 4.6 (2026) and o3 Deep Research (2026) are frontier-tier reasoning models from Anthropic and OpenAI. Claude Sonnet 4.6 ships a 1M-token context window, while o3 Deep Research ships a 200K-token context window. This comparison covers specs, pricing, capabilities, benchmarks, provider availability, and production fit. It focuses on practical selection signals rather than broad model-family marketing. The goal is to make the tradeoff clear before deeper testing.

Claude Sonnet 4.6 fits 5x more tokens; pick it for long-context work and o3 Deep Research for tighter calls.

Specs

Specification
Released2026-02-172026-01-01
Context window1M200K
Parameters
Architecturedecoder onlydecoder only
LicenseProprietaryProprietary
Knowledge cutoff2025-12-

Pricing and availability

Pricing attributeClaude Sonnet 4.6o3 Deep Research
Input price$3/1M tokens-
Output price$15/1M tokens-
Providers-

Capabilities

CapabilityClaude Sonnet 4.6o3 Deep Research
VisionYesYes
MultimodalYesYes
ReasoningYesYes
Function callingYesYes
Tool useYesYes
Structured outputsYesYes
Code executionYesNo

Benchmarks

No shared benchmark rows are currently sourced for this pair.

Deep dive

The capability footprint differs most on code execution: Claude Sonnet 4.6. Both models share vision, multimodal input, reasoning mode, and function calling, so the practical split is not just feature count. Use those differences to decide whether the page is about raw model quality, agentic coding support, multimodal ingestion, or predictable structured API behavior.

Pricing coverage is uneven: Claude Sonnet 4.6 has $3/1M input tokens and o3 Deep Research has no token price sourced yet. Provider availability is 4 tracked routes versus 0. Treat unknown pricing as an integration gap, then verify the route you will actually call before estimating production spend.

Choose Claude Sonnet 4.6 when coding workflow support, larger context windows, and broader provider choice are central to the workload. Choose o3 Deep Research when vision-heavy evaluation are more important. For production, rerun your own prompts through the exact provider, region, and tool stack you plan to ship. This keeps the decision grounded in measurable tradeoffs instead of brand-level assumptions. It also helps separate model capability from provider packaging, which can change cost and latency. For teams standardizing a stack, that distinction is often the difference between a benchmark win and a reliable deployment.

FAQ

Which has a larger context window, Claude Sonnet 4.6 or o3 Deep Research?

Claude Sonnet 4.6 supports 1M tokens, while o3 Deep Research supports 200K tokens. That gap matters most for long documents, large codebases, retrieval-heavy agents, and conversations where earlier context must remain visible.

Is Claude Sonnet 4.6 or o3 Deep Research open source?

Claude Sonnet 4.6 is listed under Proprietary. o3 Deep Research is listed under Proprietary. License labels affect whether you can self-host, redistribute weights, or rely only on hosted APIs, so confirm the upstream license before deployment.

Which is better for vision, Claude Sonnet 4.6 or o3 Deep Research?

Both Claude Sonnet 4.6 and o3 Deep Research expose vision. The better choice depends on benchmark fit, context budget, pricing, and whether your provider route exposes the same capability surface.

Which is better for multimodal input, Claude Sonnet 4.6 or o3 Deep Research?

Both Claude Sonnet 4.6 and o3 Deep Research expose multimodal input. The better choice depends on benchmark fit, context budget, pricing, and whether your provider route exposes the same capability surface.

Which is better for reasoning mode, Claude Sonnet 4.6 or o3 Deep Research?

Both Claude Sonnet 4.6 and o3 Deep Research expose reasoning mode. The better choice depends on benchmark fit, context budget, pricing, and whether your provider route exposes the same capability surface.

Where can I run Claude Sonnet 4.6 and o3 Deep Research?

Claude Sonnet 4.6 is available on OpenRouter, Anthropic, AWS Bedrock, and GCP Vertex AI. o3 Deep Research is available on the tracked providers still being sourced. Provider coverage can affect latency, region availability, compliance posture, and fallback options.

Continue comparing

Last reviewed: 2026-05-11. Data sourced from public model cards and provider documentation.