DeepSeek V4 Flash vs GPT-5.5
DeepSeek V4 Flash (2026) and GPT-5.5 (2026) are frontier-tier reasoning models from DeepSeek and OpenAI. DeepSeek V4 Flash ships a 1m-token context window, while GPT-5.5 ships a 1.05m-token context window. On MMLU PRO, GPT-5.5 leads by 1.9 pts. On pricing, DeepSeek V4 Flash costs $0.10/1M 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.
DeepSeek V4 Flash is safer overall; choose GPT-5.5 when coding workflow support matters.
Decision scorecard
Local evidence first| Signal | DeepSeek V4 Flash | GPT-5.5 |
|---|---|---|
| Best for | reasoning-heavy apps, tool-calling agents, and long-context analysis | reasoning-heavy apps, multimodal apps, and tool-calling agents |
| Decision fit | Coding, RAG, and Agents | Coding, RAG, and Agents |
| Context window | 1m | 1.05m |
| Cheapest output | $0.20/1M tokens | $30/1M tokens |
| Provider routes | 5 tracked | 4 tracked |
| Shared benchmarks | 7 shared | MMLU PRO leader |
Decision tradeoffs
- DeepSeek V4 Flash has the lower cheapest tracked output price at $0.20/1M tokens.
- DeepSeek V4 Flash has broader tracked provider coverage for fallback and procurement flexibility.
- Local decision data tags DeepSeek V4 Flash for Coding, RAG, and Agents.
- GPT-5.5 holds a shared-benchmark lead on MMLU PRO, ahead by 1.9 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 Code execution 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 V4 Flash
$128
Cheapest tracked route/tier: OpenRouter
GPT-5.5
$11,500
Cheapest tracked route/tier: OpenAI API 0-272K input tokens
Estimated monthly gap: $11,372. 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-5.5 is $29.80/1M tokens higher on cheapest tracked output pricing, so quality gains need to justify the spend.
- GPT-5.5 adds Vision, Multimodal, and Code execution in local capability data.
- Provider overlap exists on OpenRouter and Vercel AI Gateway; start route-level A/B tests there.
- DeepSeek V4 Flash is $29.80/1M tokens lower on cheapest tracked output pricing before cache, batch, or negotiated discounts.
- Check replacement coverage for Vision, Multimodal, and Code execution before moving production traffic.
Specs
| Specification | ||
|---|---|---|
| Released | 2026-04-24 | 2026-04-23 |
| Context window | 1m | 1.05m |
| Parameters | 284B | — |
| 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 | - | 2025-12 |
Pricing and availability
| Pricing attribute | DeepSeek V4 Flash | GPT-5.5 |
|---|---|---|
| Input price | $0.10/1M tokens |
|
| Output price | $0.20/1M tokens |
|
| Providers |
Capabilities
| Capability | DeepSeek V4 Flash | GPT-5.5 |
|---|---|---|
| Vision | No | Yes |
| Multimodal | No | Yes |
| Reasoning | Yes | Yes |
| Function calling | Yes | Yes |
| Tool use | Yes | Yes |
| Structured outputs | Yes | Yes |
| Code execution | No | Yes |
| IDE integration | No | No |
| Computer use | No | No |
| Parallel agents | No | No |
Benchmarks
| Benchmark | DeepSeek V4 Flash | GPT-5.5 |
|---|---|---|
| MMLU PRO | 86.2 | 88.1 |
| SWE-bench Verified | 79.0 | 82.6 |
| SWE-bench Pro | 52.6 | 58.6 |
| Google-Proof Q&A | 88.1 | 93.6 |
| HumanEval | 69.5 | 94.2 |
| Terminal-Bench 2.0 | 56.9 | 82.7 |
| Massive Multitask Language Understanding | 88.7 | 92.4 |
Deep dive
On shared benchmark coverage, MMLU PRO has DeepSeek V4 Flash at 86.2 and GPT-5.5 at 88.1, with GPT-5.5 ahead by 1.9 points; SWE-bench Verified has DeepSeek V4 Flash at 79 and GPT-5.5 at 82.6, with GPT-5.5 ahead by 3.6 points; SWE-bench Pro has DeepSeek V4 Flash at 52.6 and GPT-5.5 at 58.6, with GPT-5.5 ahead by 6 points. The largest visible gap is 6 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 vision: GPT-5.5, multimodal input: GPT-5.5, and code execution: GPT-5.5. Both models share reasoning mode, function calling, tool use, and structured outputs, 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 V4 Flash lists $0.10/1M input and $0.20/1M 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 V4 Flash lower by about $12.37 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 5 providers versus 4, so concentration risk also matters.
Choose DeepSeek V4 Flash when provider fit, 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 V4 Flash or GPT-5.5?
GPT-5.5 supports 1.05m tokens, while DeepSeek V4 Flash supports 1m 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 V4 Flash or GPT-5.5?
DeepSeek V4 Flash lists $0.10/1M input and $0.20/1M 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 V4 Flash or GPT-5.5 open source?
DeepSeek V4 Flash 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 V4 Flash 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 V4 Flash 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 V4 Flash and GPT-5.5?
DeepSeek V4 Flash is available on DeepSeek Platform, OpenRouter, Microsoft Foundry, Vercel AI Gateway, and Novita AI. 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.
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Last reviewed: 2026-06-15. Data sourced from public model cards and provider documentation.