DeepSeek R1 vs GPT-5.3-Codex
DeepSeek R1 (2025) and GPT-5.3-Codex (2026) compare a standalone API model against a coding-specialized model. DeepSeek R1 ships a 128K-token context window, while GPT-5.3-Codex ships a 400K-token context window. On SWE-bench Verified, GPT-5.3-Codex leads by 35.8 pts. On pricing, DeepSeek R1 costs $0.10/1M 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: DeepSeek R1 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 | DeepSeek R1 | GPT-5.3-Codex |
|---|---|---|
| Product type | Standalone API model | Coding-specialized model |
| Best for | reasoning-heavy apps and provider-routed production | custom coding agents, code generation, and tool loops |
| Decision fit | Coding, RAG, and Agents | Coding, RAG, and Agents |
| Context window | 128K | 400K |
| Cheapest output | $0.30/1M tokens | $14/1M tokens |
| Provider routes | 14 tracked | 3 tracked |
| Shared benchmarks | 1 rows | SWE-bench Verified leader |
Decision tradeoffs
- DeepSeek R1 has the lower cheapest tracked output price at $0.30/1M tokens.
- DeepSeek R1 has broader tracked provider coverage for fallback and procurement flexibility.
- Local decision data tags DeepSeek R1 for Coding, RAG, and Agents.
- GPT-5.3-Codex leads the largest shared benchmark signal on SWE-bench Verified by 35.8 points.
- GPT-5.3-Codex has the larger context window for long prompts, retrieval packs, or transcript analysis.
- GPT-5.3-Codex uniquely exposes Vision, Function calling, and Tool use in local model data.
- 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.
DeepSeek R1
$155
Cheapest tracked route/tier: Bitdeer AI
GPT-5.3-Codex
$4,900
Cheapest tracked route/tier: OpenRouter
Estimated monthly gap: $4,745. Batch, cache, alternate speed tiers, and negotiated pricing are excluded from this local estimate.
Switch friction
- Provider overlap exists on OpenRouter and Vercel AI Gateway; start route-level A/B tests there.
- GPT-5.3-Codex is $13.70/1M tokens higher on cheapest tracked output pricing, so quality gains need to justify the spend.
- GPT-5.3-Codex adds Vision, Function calling, and Tool use in local capability data.
- Provider overlap exists on OpenRouter and Vercel AI Gateway; start route-level A/B tests there.
- DeepSeek R1 is $13.70/1M tokens lower on cheapest tracked output pricing before cache, batch, or negotiated discounts.
- Check replacement coverage for Vision, Function calling, and Tool use before moving production traffic.
Specs
| Specification | ||
|---|---|---|
| Released | 2025-01-20 | 2026-02-05 |
| Context window | 128K | 400K |
| Parameters | 671B, 37B Active | — |
| Architecture | decoder only | decoder only |
| License | Open Source | Proprietary |
| Knowledge cutoff | 2023-12 | 2025-08 |
Pricing and availability
| Pricing attribute | DeepSeek R1 | GPT-5.3-Codex |
|---|---|---|
| Input price | $0.10/1M tokens | $1.75/1M tokens |
| Output price | $0.30/1M tokens | $14/1M tokens |
| Providers |
Capabilities
| Capability | DeepSeek R1 | GPT-5.3-Codex |
|---|---|---|
| Vision | No | Yes |
| Multimodal | No | No |
| Reasoning | Yes | Yes |
| Function calling | No | Yes |
| Tool use | No | Yes |
| Structured outputs | Yes | Yes |
| Code execution | Yes | Yes |
| IDE integration | No | No |
| Computer use | No | No |
| Parallel agents | No | No |
Benchmarks
| Benchmark | DeepSeek R1 | GPT-5.3-Codex |
|---|---|---|
| SWE-bench Verified | 49.2 | 85.0 |
Deep dive
On shared benchmark coverage, SWE-bench Verified has DeepSeek R1 at 49.2 and GPT-5.3-Codex at 85, with GPT-5.3-Codex ahead by 35.8 points. The largest visible gap is 35.8 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 vision: GPT-5.3-Codex, function calling: GPT-5.3-Codex, and tool use: GPT-5.3-Codex. Both models share reasoning mode, structured outputs, and code execution, 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, DeepSeek R1 lists $0.10/1M input and $0.30/1M 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 DeepSeek R1 lower by about $5.26 per million blended tokens. Availability is 14 providers versus 3, so concentration risk also matters.
Choose DeepSeek R1 when coding workflow support, lower input-token cost, and broader provider choice are central to the workload. Choose GPT-5.3-Codex when coding workflow support and larger context windows 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, DeepSeek R1 or GPT-5.3-Codex?
GPT-5.3-Codex supports 400K tokens, while DeepSeek R1 supports 128K tokens. That gap matters most for long documents, large codebases, retrieval-heavy agents, and conversations where earlier context must remain visible. Use this as a quick comparison signal, then confirm the provider-specific limits before committing to production.
Which is cheaper, DeepSeek R1 or GPT-5.3-Codex?
DeepSeek R1 is cheaper on tracked token pricing. DeepSeek R1 costs $0.10/1M input and $0.30/1M 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 DeepSeek R1 or GPT-5.3-Codex open source?
DeepSeek R1 is listed under Open Source. 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, DeepSeek R1 or GPT-5.3-Codex?
GPT-5.3-Codex has the clearer documented vision signal in this comparison. If vision is mission-critical, validate it against the provider endpoint because model-level support and API-level exposure can differ. Use this as a quick comparison signal, then confirm the provider-specific limits before committing to production.
Which is better for reasoning mode, DeepSeek R1 or GPT-5.3-Codex?
Both DeepSeek R1 and GPT-5.3-Codex expose reasoning mode. 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.
Where can I run DeepSeek R1 and GPT-5.3-Codex?
DeepSeek R1 is available on DeepSeek Platform, OpenRouter, Together AI, Fireworks AI, and NVIDIA NIM. 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.
Continue comparing
Last reviewed: 2026-05-22. Data sourced from public model cards and provider documentation.