DeepSeek R1 0528 vs GPT-5.5
DeepSeek R1 0528 (2025) and GPT-5.5 (2026) are frontier-tier reasoning models from DeepSeek and OpenAI. DeepSeek R1 0528 ships a 130k-token context window, while GPT-5.5 ships a 1.05m-token context window. On MMLU PRO, GPT-5.5 leads by 3.1 pts. On pricing, DeepSeek R1 0528 costs $0.50/1M input tokens; GPT-5.5 ranges from $5 to $8/1M input tokens by tier. This comparison covers specs, pricing, API access, capabilities, benchmarks, input and output token costs, and production fit for coding and agent workloads.
GPT-5.5 fits 8x more tokens; pick it for long-context work and DeepSeek R1 0528 for tighter calls.
Decision scorecard
Local evidence first| Signal | DeepSeek R1 0528 | GPT-5.5 |
|---|---|---|
| Best for | reasoning-heavy apps and provider-routed production | reasoning-heavy apps, multimodal apps, and tool-calling agents |
| Decision fit | Coding, RAG, and Agents | Coding, RAG, and Agents |
| Context window | 130k | 1.05m |
| Cheapest output | $2.15/1M tokens | $30/1M tokens |
| Provider routes | 7 tracked | 4 tracked |
| Shared benchmarks | 5 shared | MMLU PRO leader |
Decision tradeoffs
- DeepSeek R1 0528 holds a shared-benchmark lead on AIME 2025, ahead by 6.3 points.
- DeepSeek R1 0528 has the lower cheapest tracked output price at $2.15/1M tokens.
- DeepSeek R1 0528 has broader tracked provider coverage for fallback and procurement flexibility.
- Local decision data tags DeepSeek R1 0528 for Coding, RAG, and Agents.
- GPT-5.5 holds a shared-benchmark lead on MMLU PRO, ahead by 3.1 points.
- GPT-5.5 has the larger context window for long prompts, retrieval packs, or transcript analysis.
- GPT-5.5 uniquely exposes Vision, Multimodal, and Function calling in local model data.
- Local decision data tags GPT-5.5 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 0528
$938
Cheapest tracked route/tier: OpenRouter
GPT-5.5
$11,500
Cheapest tracked route/tier: OpenAI API 0-272K input tokens
Estimated monthly gap: $10,563. Batch, cache, alternate speed tiers, and negotiated pricing are excluded from this local estimate.
Switch friction
- Provider overlap exists on OpenRouter; start route-level A/B tests there.
- GPT-5.5 is $27.85/1M tokens higher on cheapest tracked output pricing, so quality gains need to justify the spend.
- GPT-5.5 adds Vision, Multimodal, and Function calling in local capability data.
- Provider overlap exists on OpenRouter; start route-level A/B tests there.
- DeepSeek R1 0528 is $27.85/1M tokens lower on cheapest tracked output pricing before cache, batch, or negotiated discounts.
- Check replacement coverage for Vision, Multimodal, and Function calling before moving production traffic.
Specs
| Specification | ||
|---|---|---|
| Released | 2025-05-28 | 2026-04-23 |
| Context window | 130k | 1.05m |
| Parameters | 685B total, 37B active (MoE) | — |
| Architecture | Decoder Only | Decoder Only |
| License | MIT(OSI) | Proprietary |
| Openness | Open source | Proprietary |
| Commercial use | Commercial use allowed | Commercial use with conditions |
| Knowledge cutoff | - | 2025-12 |
Pricing and availability
| Pricing attribute | DeepSeek R1 0528 | GPT-5.5 |
|---|---|---|
| Input price | $0.50/1M tokens |
|
| Output price | $2.15/1M tokens |
|
| Providers |
Capabilities
| Capability | DeepSeek R1 0528 | GPT-5.5 |
|---|---|---|
| Vision | No | Yes |
| Multimodal | No | Yes |
| 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 0528 | GPT-5.5 |
|---|---|---|
| MMLU PRO | 85.0 | 88.1 |
| SWE-bench Verified | 57.6 | 82.6 |
| Google-Proof Q&A | 81.0 | 93.6 |
| AIME 2025 | 87.5 | 81.2 |
| Aider Polyglot | 71.4 | 88.0 |
Deep dive
On shared benchmark coverage, MMLU PRO has DeepSeek R1 0528 at 85 and GPT-5.5 at 88.1, with GPT-5.5 ahead by 3.1 points; SWE-bench Verified has DeepSeek R1 0528 at 57.6 and GPT-5.5 at 82.6, with GPT-5.5 ahead by 25.0 points; Google-Proof Q&A has DeepSeek R1 0528 at 81 and GPT-5.5 at 93.6, with GPT-5.5 ahead by 12.6 points. The largest visible gap is 25.0 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-5.5, multimodal input: GPT-5.5, function calling: GPT-5.5, and tool use: GPT-5.5. 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 0528 lists $0.50/1M input and $2.15/1M output tokens on the cheapest tracked provider, while GPT-5.5 lists tiered pricing: 0-272K input tokens is $5/1M input and $30/1M output; 272K+ input tokens is $8/1M input and $36/1M output. A 70/30 input-output blend puts DeepSeek R1 0528 lower by about $11.51 per million blended tokens. For tiered rows, this cheapest-track view can understate interactive or fast-lane spend, so compare the tier you will actually use. Availability is 7 providers versus 4, so concentration risk also matters.
Choose DeepSeek R1 0528 when coding workflow support, lower input-token cost, and broader provider choice are central to the workload. Choose GPT-5.5 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 0528 or GPT-5.5?
GPT-5.5 supports 1.05m tokens, while DeepSeek R1 0528 supports 130k 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 R1 0528 or GPT-5.5?
DeepSeek R1 0528 lists $0.50/1M input and $2.15/1M output tokens on the cheapest tracked provider. GPT-5.5 lists tiered pricing: 0-272K input tokens is $5/1M input and $30/1M output; 272K+ input tokens is $8/1M input and $36/1M output. Compare the tier you will actually use; cheap async pricing can overstate savings for interactive workflows. Provider discounts or batch pricing can still change the final bill.
Is DeepSeek R1 0528 or GPT-5.5 open source?
DeepSeek R1 0528 is listed under MIT. GPT-5.5 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 0528 or GPT-5.5?
GPT-5.5 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 multimodal input, DeepSeek R1 0528 or GPT-5.5?
GPT-5.5 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 DeepSeek R1 0528 and GPT-5.5?
DeepSeek R1 0528 is available on Together AI, Fireworks AI, GCP Vertex AI, Novita AI, and OpenRouter. GPT-5.5 is available on OpenAI API, OpenRouter, Vercel AI Gateway, and AWS Bedrock. Provider coverage can affect latency, region availability, compliance posture, and fallback options.
Continue comparing
Last reviewed: 2026-06-15. Data sourced from public model cards and provider documentation.