DeepSeek V3.1 vs GPT-5.2 Codex
DeepSeek V3.1 (2025) and GPT-5.2 Codex (2025) compare a standalone API model against a coding-specialized model. DeepSeek V3.1 ships a 64k-token context window, while GPT-5.2 Codex ships a 400k-token context window. On SWE-bench Verified, GPT-5.2 Codex leads by 6.8 pts. On pricing, DeepSeek V3.1 costs $0.27/1M 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 V3.1 is standalone API model, while GPT-5.2 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 V3.1 | GPT-5.2 Codex |
|---|---|---|
| Product type | Standalone API model | Coding-specialized model |
| Best for | multimodal apps and provider-routed production | custom coding agents, code generation, and tool loops |
| Decision fit | Coding, Agents, and Vision | Coding, RAG, and Agents |
| Context window | 64k | 400k |
| Cheapest output | $1/1M tokens | $14/1M tokens |
| Provider routes | 8 tracked | 2 tracked |
| Shared benchmarks | 1 shared | SWE-bench Verified leader |
Decision tradeoffs
- DeepSeek V3.1 has the lower cheapest tracked output price at $1/1M tokens.
- DeepSeek V3.1 has broader tracked provider coverage for fallback and procurement flexibility.
- Local decision data tags DeepSeek V3.1 for Coding, Agents, and Vision.
- GPT-5.2 Codex holds a shared-benchmark lead on SWE-bench Verified, ahead by 6.8 points.
- GPT-5.2 Codex has the larger context window for long prompts, retrieval packs, or transcript analysis.
- GPT-5.2 Codex uniquely exposes Reasoning, Function calling, and Tool use in local model data.
- Local decision data tags GPT-5.2 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 V3.1
$466
Cheapest tracked route/tier: Novita AI
GPT-5.2 Codex
$4,900
Cheapest tracked route/tier: Vercel AI Gateway
Estimated monthly gap: $4,434. Batch, cache, alternate speed tiers, and negotiated pricing are excluded from this local estimate.
Switch friction
- Provider overlap exists on Vercel AI Gateway; start route-level A/B tests there.
- GPT-5.2 Codex is $13/1M tokens higher on cheapest tracked output pricing, so quality gains need to justify the spend.
- GPT-5.2 Codex adds Reasoning, Function calling, and Tool use in local capability data.
- Provider overlap exists on Vercel AI Gateway; start route-level A/B tests there.
- DeepSeek V3.1 is $13/1M tokens lower on cheapest tracked output pricing before cache, batch, or negotiated discounts.
- Check replacement coverage for Reasoning, Function calling, and Tool use before moving production traffic.
Specs
| Specification | ||
|---|---|---|
| Released | 2025-08-21 | 2025-12-18 |
| Context window | 64k | 400k |
| Parameters | 671B total, 37B active (MoE) | — |
| Architecture | Mixture of Experts | Decoder Only |
| License | MITOSI-approved | Proprietary |
| Openness | Open source | Proprietary |
| Weights | Unknown | Not released |
| Code | Unknown | Unknown |
| Commercial use | Commercial use: permitted | Commercial use: conditional |
| Knowledge cutoff | - | 2025-08 |
Pricing and availability
| Pricing attribute | DeepSeek V3.1 | GPT-5.2 Codex |
|---|---|---|
| Input price | $0.27/1M tokens | $1.75/1M tokens |
| Output price | $1/1M tokens | $14/1M tokens |
| Providers |
Capabilities
| Capability | DeepSeek V3.1 | GPT-5.2 Codex |
|---|---|---|
| Vision | Yes | Yes |
| Multimodal | Yes | Yes |
| Reasoning | No | 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 V3.1 | GPT-5.2 Codex |
|---|---|---|
| SWE-bench Verified | 66.0 | 72.8 |
Deep dive
On shared benchmark coverage, SWE-bench Verified has DeepSeek V3.1 at 66 and GPT-5.2 Codex at 72.8, with GPT-5.2 Codex ahead by 6.8 points. The largest visible gap is 6.8 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 reasoning mode: GPT-5.2 Codex, function calling: GPT-5.2 Codex, and tool use: GPT-5.2 Codex. Both models share vision, multimodal input, 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 V3.1 lists $0.27/1M input and $1/1M output tokens on the cheapest tracked provider, while GPT-5.2 Codex lists $1.75/1M input and $14/1M output tokens on the cheapest tracked provider. A 70/30 input-output blend puts DeepSeek V3.1 lower by about $4.94 per million blended tokens. Availability is 8 providers versus 2, so concentration risk also matters.
Choose DeepSeek V3.1 when coding workflow support, lower input-token cost, and broader provider choice are central to the workload. Choose GPT-5.2 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 V3.1 or GPT-5.2 Codex?
GPT-5.2 Codex supports 400k tokens, while DeepSeek V3.1 supports 64k tokens. That gap matters most for long documents, large codebases, retrieval-heavy agents, and conversations where earlier context must remain visible.
Which is cheaper, DeepSeek V3.1 or GPT-5.2 Codex?
DeepSeek V3.1 is cheaper on tracked token pricing. DeepSeek V3.1 costs $0.27/1M input and $1/1M output tokens. GPT-5.2 Codex costs $1.75/1M input and $14/1M output tokens. Provider discounts or batch pricing can still change the final bill.
Is DeepSeek V3.1 or GPT-5.2 Codex open source?
DeepSeek V3.1 is listed under MIT. GPT-5.2 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 V3.1 or GPT-5.2 Codex?
Both DeepSeek V3.1 and GPT-5.2 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, DeepSeek V3.1 or GPT-5.2 Codex?
Both DeepSeek V3.1 and GPT-5.2 Codex expose multimodal input. 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 V3.1 and GPT-5.2 Codex?
DeepSeek V3.1 is available on Microsoft Foundry, Fireworks AI, NVIDIA NIM, Together AI, and AWS Bedrock. GPT-5.2 Codex is available on Vercel AI Gateway and OpenAI API. Provider coverage can affect latency, region availability, compliance posture, and fallback options.
Continue comparing
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Last reviewed: 2026-06-30. Data sourced from public model cards and provider documentation.