Claude 3.7 Sonnet vs GPT-5.3-Codex

Claude 3.7 Sonnet (2024) and GPT-5.3-Codex (2026) compare a standalone API model against a coding-specialized model. Claude 3.7 Sonnet ships a 200k-token context window, while GPT-5.3-Codex ships a 400k-token context window. On SWE-bench Verified, GPT-5.3-Codex leads by 14.7 pts. On pricing, GPT-5.3-Codex costs $1.75/1M input tokens versus $3/1M for the alternative. This page treats the result as workflow and deployment fit, not a universal model winner.

Treat this as a product-type comparison: Claude 3.7 Sonnet is standalone API model, while GPT-5.3-Codex is coding-specialized model. Choose based on workflow fit before reading any benchmark or price row as decisive.

Decision scorecard

Local evidence first

Signal	Claude 3.7 Sonnet	GPT-5.3-Codex	How to read it
Product type	Standalone API model	Coding-specialized model	Read downstream rows through the product-type lens before comparing benchmarks, prices, or provider availability.
Best for	reasoning-heavy apps, multimodal apps, and tool-calling agents	custom coding agents, code generation, and tool loops	Use-case synthesis from product type, capability flags, context, and provider data.
Decision fit	Coding, RAG, and Agents	Coding, RAG, and Agents	Primary workload tags from local decision data.
Context window	200k	400k	Higher is better when prompts, retrieval chunks, or transcripts are large.
Cheapest output	$15/1M tokens	$14/1M tokens	Cheapest tracked provider route; verify your exact region and tier.
Provider routes	6 tracked	3 tracked	Broader coverage can reduce vendor lock-in and fallback risk.
Shared benchmarks	1 rows	SWE-bench Verified leader	Largest visible lead is 14.7 points on SWE-bench Verified.

Decision tradeoffs

Choose Claude 3.7 Sonnet when...

Claude 3.7 Sonnet has broader tracked provider coverage for fallback and procurement flexibility.
Claude 3.7 Sonnet uniquely exposes Multimodal in local model data.
Local decision data tags Claude 3.7 Sonnet for Coding, RAG, and Agents.

Choose GPT-5.3-Codex when...

GPT-5.3-Codex leads the largest shared benchmark signal on SWE-bench Verified by 14.7 points.
GPT-5.3-Codex has the larger context window for long prompts, retrieval packs, or transcript analysis.
GPT-5.3-Codex has the lower cheapest tracked output price at $14/1M tokens.
Local decision data tags GPT-5.3-Codex for Coding, RAG, and Agents.

Monthly cost at traffic

Estimate token spend from the cheapest tracked input and output route or tier on this page.

Lower estimate GPT-5.3-Codex

Requests / monthInput tokens / requestOutput tokens / request

Claude 3.7 Sonnet

$6,150

Cheapest tracked route/tier: GCP Vertex AI

GPT-5.3-Codex

$4,900

Cheapest tracked route/tier: OpenRouter

Estimated monthly gap: $1,250. Batch, cache, alternate speed tiers, and negotiated pricing are excluded from this local estimate.

Switch friction

Claude 3.7 Sonnet -> GPT-5.3-Codex

Provider overlap exists on OpenRouter; start route-level A/B tests there.
GPT-5.3-Codex is $1/1M tokens lower on cheapest tracked output pricing before cache, batch, or negotiated discounts.
Check replacement coverage for Multimodal before moving production traffic.

GPT-5.3-Codex -> Claude 3.7 Sonnet

Provider overlap exists on OpenRouter; start route-level A/B tests there.
Claude 3.7 Sonnet is $1/1M tokens higher on cheapest tracked output pricing, so quality gains need to justify the spend.
Claude 3.7 Sonnet adds Multimodal in local capability data.

Specs

Specification	Claude 3.7 Sonnet Anthropic	GPT-5.3-Codex OpenAI
Released	2024-03-04	2026-02-05
Context window	200k	400k
Parameters	—	—
Architecture	decoder only	decoder only
License	Proprietary	Proprietary
Knowledge cutoff	2024-11	2025-08

Pricing and availability

Pricing attribute	Claude 3.7 Sonnet	GPT-5.3-Codex
Input price	$3/1M tokens	$1.75/1M tokens
Output price	$15/1M tokens	$14/1M tokens
Providers	Snowflake Cortex GCP Vertex AI Replicate API OpenRouter AWS Bedrock Anthropic	OpenRouter OpenAI API Vercel AI Gateway

Capabilities

Capability	Claude 3.7 Sonnet	GPT-5.3-Codex
Vision	Yes	Yes
Multimodal	Yes	No
Reasoning	Yes	Yes
Function calling	Yes	Yes
Tool use	Yes	Yes
Structured outputs	Yes	Yes
Code execution	Yes	Yes
IDE integration	No	No
Computer use	No	No
Parallel agents	No	No

Benchmarks

Benchmark	Claude 3.7 Sonnet	GPT-5.3-Codex
SWE-bench Verified	70.3	85.0

Deep dive

On shared benchmark coverage, SWE-bench Verified has Claude 3.7 Sonnet at 70.3 and GPT-5.3-Codex at 85, with GPT-5.3-Codex ahead by 14.7 points. The largest visible gap is 14.7 points on SWE-bench Verified, which matters most when that benchmark mirrors your workload. Treat isolated benchmark wins as directional, because provider routing, prompt style, and tool access can move real application results.

The capability footprint differs most on multimodal input: Claude 3.7 Sonnet. Both models share vision, reasoning mode, function calling, and tool use, 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.

For cost, Claude 3.7 Sonnet lists $3/1M input and $15/1M output tokens on the cheapest tracked provider, while GPT-5.3-Codex lists $1.75/1M input and $14/1M output tokens on the cheapest tracked provider. A 70/30 input-output blend puts GPT-5.3-Codex lower by about $1.17 per million blended tokens. Availability is 6 providers versus 3, so concentration risk also matters.

Choose Claude 3.7 Sonnet when coding workflow support and broader provider choice are central to the workload. Choose GPT-5.3-Codex when coding workflow support, larger context windows, and lower input-token cost are more important. For production, rerun your own prompts through the exact provider, region, and tool stack you plan to ship.

FAQ

Which has a larger context window, Claude 3.7 Sonnet or GPT-5.3-Codex?

GPT-5.3-Codex supports 400k tokens, while Claude 3.7 Sonnet supports 200k tokens. That gap matters most for long documents, large codebases, retrieval-heavy agents, and conversations where earlier context must remain visible.

Which is cheaper, Claude 3.7 Sonnet or GPT-5.3-Codex?

GPT-5.3-Codex is cheaper on tracked token pricing. Claude 3.7 Sonnet costs $3/1M input and $15/1M output tokens. GPT-5.3-Codex costs $1.75/1M input and $14/1M output tokens. Provider discounts or batch pricing can still change the final bill.

Is Claude 3.7 Sonnet or GPT-5.3-Codex open source?

Claude 3.7 Sonnet is listed under Proprietary. GPT-5.3-Codex 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 3.7 Sonnet or GPT-5.3-Codex?

Both Claude 3.7 Sonnet and GPT-5.3-Codex expose vision. The better choice depends on benchmark fit, context budget, pricing, and whether your provider route exposes the same capability surface. Use this as a quick comparison signal, then confirm the provider-specific limits before committing to production.

Which is better for multimodal input, Claude 3.7 Sonnet or GPT-5.3-Codex?

Claude 3.7 Sonnet has the clearer documented multimodal input signal in this comparison. If multimodal input is mission-critical, validate it against the provider endpoint because model-level support and API-level exposure can differ.

Where can I run Claude 3.7 Sonnet and GPT-5.3-Codex?

Claude 3.7 Sonnet is available on Snowflake Cortex, GCP Vertex AI, Replicate API, OpenRouter, and AWS Bedrock. GPT-5.3-Codex is available on OpenRouter, OpenAI API, and Vercel AI Gateway. Provider coverage can affect latency, region availability, compliance posture, and fallback options.

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Last reviewed: 2026-05-22. Data sourced from public model cards and provider documentation.