DeepSeek V4 vs GPT-5.5
Open MIT-licensed weights against the closed flagship — a comparison that comes down to cost, control and agentic reliability.
DeepSeek V4 vs GPT-5.5: side-by-side
| DeepSeek V4-Pro | GPT-5.5 "Spud" | |
|---|---|---|
| Maker | DeepSeek (China) | OpenAI |
| Released | 24 April 2026 | 23 April 2026 |
| Licence | MIT — open weights | Closed — API only |
| Architecture | MoE · 1.6T params (49B active) | Unified multimodal retrain |
| Context window | 1M tokens | 1M tokens (400K in Codex CLI) |
| API price (per 1M) | $1.74 in / $3.48 out | $5 in / $30 out |
| Self-hostable | Yes — Hugging Face & ModelScope | No |
| Best at | Coding, low-cost agentic work | Agentic coding, computer use, deep research |
Benchmark comparison
Both models sit at the coding frontier. DeepSeek V4-Pro posts an exceptional SWE-bench Verified score and the highest competitive-programming rating of any model at release; GPT-5.5 leads on agentic, multi-step tool benchmarks.
| Benchmark | DeepSeek V4-Pro | GPT-5.5 |
|---|---|---|
| SWE-bench Verified | 80.6% | — |
| SWE-bench Pro | — | 58.6% |
| Codeforces rating | 3,206 | — (GPT-5.4: 3,168) |
| Terminal-Bench 2.0 | — | 82.7% |
Reading the benchmarks
The two models are measured on different test variants, so scores are not directly comparable cell-for-cell. The honest summary: DeepSeek V4-Pro is elite at raw coding and competitive programming, while GPT-5.5 is purpose-built for long agentic chains and computer-use tasks.
The cost gap
This is the comparison's headline. DeepSeek V4-Pro costs $1.74 / $3.48 per 1M input/output tokens; GPT-5.5 costs $5 / $30. On output tokens — usually the bigger share of a real bill — V4-Pro is roughly 8-9x cheaper. Drop to V4-Flash ($0.14 / $0.28) and the gap widens past 100x for workloads that tolerate the smaller model. For any high-volume production system, that difference reshapes the economics.
Open weights vs closed API
DeepSeek V4 is MIT-licensed with weights on Hugging Face and ModelScope — you can download, fine-tune, self-host and deploy commercially with no per-token fees and no vendor dependency. GPT-5.5 is closed: it exists only behind OpenAI's API and apps. For teams with data-residency rules, air-gapped environments, or a strategic aversion to lock-in, that single difference can decide the choice before benchmarks enter the picture.
Which should you use?
- Cost-sensitive or high-volume workloads → DeepSeek V4 — 8-10x cheaper, frontier-class coding.
- Self-hosting, fine-tuning or data residency → DeepSeek V4 — open MIT weights.
- Agentic, multi-step automation and computer use → GPT-5.5 — built for it, with Codex integration.
- Managed, zero-ops deployment → GPT-5.5 — no infrastructure to run.
Full DeepSeek V4 overview Full GPT-5.5 overview
Frequently asked questions
Is DeepSeek V4 better than GPT-5.5?
DeepSeek V4-Pro scores higher on SWE-bench Verified (80.6%) and costs about a tenth as much per output token. GPT-5.5 leads on agentic, multi-step benchmarks like Terminal-Bench 2.0 (82.7%) and offers a managed Codex environment. DeepSeek V4 wins on cost and open weights; GPT-5.5 wins on agentic reliability.
How much cheaper is DeepSeek V4 than GPT-5.5?
DeepSeek V4-Pro costs $1.74 per million input tokens and $3.48 per million output tokens, versus $5 and $30 for GPT-5.5 — making V4-Pro output roughly 8-9x cheaper. V4-Flash is cheaper still at $0.14 / $0.28.
Can I self-host DeepSeek V4 but not GPT-5.5?
Yes. DeepSeek V4 is released under the MIT License with open weights on Hugging Face and ModelScope, so it can be self-hosted and fine-tuned. GPT-5.5 is closed and available only through OpenAI's API and apps.
Which is better for coding?
Both are frontier-class. DeepSeek V4-Pro scores 80.6% on SWE-bench Verified and has the highest Codeforces rating of any model at release (3,206). GPT-5.5 leads on agentic, multi-step coding tasks and integrates with the Codex environment.