GPT-5.3-Codex vs Step 3.7 Flash

Name: GPT-5.3-Codex
Author: OpenAI

GPT-5.3-Codex (2026) and Step 3.7 Flash (2026) compare a coding-specialized model against a standalone API model. GPT-5.3-Codex ships a 400k-token context window, while Step 3.7 Flash ships a 256k-token context window. On SWE-bench Pro, GPT-5.3-Codex leads by 0.5 pts. On pricing, Step 3.7 Flash costs $0.20/1M input tokens versus $1.75/1M 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: GPT-5.3-Codex is coding-specialized model, while Step 3.7 Flash is standalone API model. Choose based on workflow fit before reading any benchmark or price row as decisive.

Decision scorecard

Local evidence first

Signal	GPT-5.3-Codex	Step 3.7 Flash	How to read it
Product type	Coding-specialized model	Standalone API model	Read downstream rows through the product-type lens before comparing benchmarks, prices, or provider availability.
Best for	custom coding agents, code generation, and tool loops	reasoning-heavy apps, multimodal apps, and tool-calling agents	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	400k	256k	Higher is better when prompts, retrieval chunks, or transcripts are large.
Cheapest output	$14/1M tokens	$1.15/1M tokens	Cheapest tracked provider route; verify your exact region and tier.
Provider routes	3 tracked	3 tracked	Broader coverage can reduce vendor lock-in and fallback risk.
Shared benchmarks	SWE-bench Pro leader	1 rows	Visible benchmark lead is 0.5 points on SWE-bench Pro.

Decision tradeoffs

Choose GPT-5.3-Codex when...

GPT-5.3-Codex holds a shared-benchmark lead on SWE-bench Pro, ahead by 0.5 points.
GPT-5.3-Codex has the larger context window for long prompts, retrieval packs, or transcript analysis.
GPT-5.3-Codex uniquely exposes Code execution and Computer use in local model data.
Local decision data tags GPT-5.3-Codex for Coding, RAG, and Agents.

Choose Step 3.7 Flash when...

Step 3.7 Flash has the lower cheapest tracked output price at $1.15/1M tokens.
Step 3.7 Flash uniquely exposes Multimodal in local model data.
Local decision data tags Step 3.7 Flash 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 Step 3.7 Flash

Requests / monthInput tokens / requestOutput tokens / request

GPT-5.3-Codex

$4,900

Cheapest tracked route/tier: OpenRouter

Step 3.7 Flash

$448

Cheapest tracked route/tier: StepFun

Estimated monthly gap: $4,453. Batch, cache, alternate speed tiers, and negotiated pricing are excluded from this local estimate.

Switch friction

GPT-5.3-Codex -> Step 3.7 Flash

Provider overlap exists on OpenRouter; start route-level A/B tests there.
Step 3.7 Flash is $12.85/1M tokens lower on cheapest tracked output pricing before cache, batch, or negotiated discounts.
Check replacement coverage for Code execution and Computer use before moving production traffic.
Step 3.7 Flash adds Multimodal in local capability data.

Step 3.7 Flash -> GPT-5.3-Codex

Provider overlap exists on OpenRouter; start route-level A/B tests there.
GPT-5.3-Codex is $12.85/1M tokens higher on cheapest tracked output pricing, so quality gains need to justify the spend.
Check replacement coverage for Multimodal before moving production traffic.
GPT-5.3-Codex adds Code execution and Computer use in local capability data.

Specs

Specification	GPT-5.3-Codex OpenAI	Step 3.7 Flash StepFun
Released	2026-02-05	2026-05-29
Context window	400k	256k
Parameters	—	198B (11B active)
Architecture	decoder only	mixture of experts
License	Proprietary	Proprietary
Openness	Proprietary	Proprietary
Commercial use	Commercial use with conditions	Commercial use with conditions
Knowledge cutoff	2025-08	-

Pricing and availability

Pricing attribute	GPT-5.3-Codex	Step 3.7 Flash
Input price	$1.75/1M tokens	$0.20/1M tokens
Output price	$14/1M tokens	$1.15/1M tokens
Providers	OpenRouter OpenAI API Vercel AI Gateway	StepFun OpenRouter NVIDIA NIM

Capabilities

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

Benchmarks

Benchmark	GPT-5.3-Codex	Step 3.7 Flash
SWE-bench Pro	56.8	56.3

Deep dive

On shared benchmark coverage, SWE-bench Pro has GPT-5.3-Codex at 56.8 and Step 3.7 Flash at 56.3, with GPT-5.3-Codex ahead by 0.5 points. The largest visible gap is 0.5 points on SWE-bench Pro, 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: Step 3.7 Flash and code execution: GPT-5.3-Codex. 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, GPT-5.3-Codex lists $1.75/1M input and $14/1M output tokens on the cheapest tracked provider, while Step 3.7 Flash lists $0.20/1M input and $1.15/1M output tokens on the cheapest tracked provider. A 70/30 input-output blend puts Step 3.7 Flash lower by about $4.94 per million blended tokens. Availability is 3 providers versus 3, so concentration risk also matters.

Choose GPT-5.3-Codex when coding workflow support and larger context windows are central to the workload. Choose Step 3.7 Flash when vision-heavy evaluation 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, GPT-5.3-Codex or Step 3.7 Flash?

GPT-5.3-Codex supports 400k tokens, while Step 3.7 Flash supports 256k tokens. That gap matters most for long documents, large codebases, retrieval-heavy agents, and conversations where earlier context must remain visible.

Which is cheaper, GPT-5.3-Codex or Step 3.7 Flash?

Step 3.7 Flash is cheaper on tracked token pricing. GPT-5.3-Codex costs $1.75/1M input and $14/1M output tokens. Step 3.7 Flash costs $0.20/1M input and $1.15/1M output tokens. Provider discounts or batch pricing can still change the final bill.

Is GPT-5.3-Codex or Step 3.7 Flash open source?

GPT-5.3-Codex is listed under Proprietary. Step 3.7 Flash 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, GPT-5.3-Codex or Step 3.7 Flash?

Both GPT-5.3-Codex and Step 3.7 Flash 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, GPT-5.3-Codex or Step 3.7 Flash?

Step 3.7 Flash 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 GPT-5.3-Codex and Step 3.7 Flash?

GPT-5.3-Codex is available on OpenRouter, OpenAI API, and Vercel AI Gateway. Step 3.7 Flash is available on StepFun, OpenRouter, and NVIDIA NIM. Provider coverage can affect latency, region availability, compliance posture, and fallback options.

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Last reviewed: 2026-06-10. Data sourced from public model cards and provider documentation.

Both models

GPT-5.3-Codex Step 3.7 Flash