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 not-yet-sourced context window. 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, Agents, and Vision |
| Context window | 64k | — |
| Cheapest output | $1/1M tokens | $14/1M tokens |
| Provider routes | 8 tracked | 1 tracked |
| Shared benchmarks | 0 rows | 0 rows |
Decision tradeoffs
- DeepSeek V3.1 has the larger context window for long prompts, retrieval packs, or transcript analysis.
- 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.
- DeepSeek V3.1 uniquely exposes Structured outputs in local model data.
- Local decision data tags DeepSeek V3.1 for Coding, Agents, and Vision.
- 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, Agents, and Vision.
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.
- Check replacement coverage for Structured outputs before moving production traffic.
- 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.
- DeepSeek V3.1 adds Structured outputs in local capability data.
Specs
| Specification | ||
|---|---|---|
| Released | 2025-08-21 | 2025-12-18 |
| Context window | 64k | — |
| Parameters | 671B total, 37B active (MoE) | — |
| Architecture | mixture of experts | decoder only |
| License | MIT(OSI) | Proprietary |
| Openness | Open source | Proprietary |
| Commercial use | Commercial use allowed | Commercial use with conditions |
| 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 | No |
| Code execution | Yes | Yes |
| IDE integration | No | No |
| Computer use | No | No |
| Parallel agents | No | No |
Benchmarks
No shared benchmark rows are currently sourced for this pair.
Deep dive
The capability footprint differs most on reasoning mode: GPT-5.2 Codex, function calling: GPT-5.2 Codex, tool use: GPT-5.2 Codex, and structured outputs: DeepSeek V3.1. Both models share vision, multimodal input, 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 1, 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 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.
FAQ
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.
Which is better for reasoning mode, DeepSeek V3.1 or GPT-5.2 Codex?
GPT-5.2 Codex has the clearer documented reasoning mode signal in this comparison. If reasoning mode is mission-critical, validate it against the provider endpoint because model-level support and API-level exposure can differ.
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. 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.