GPT-5.5 vs DeepSeek-V4-Flash
GPT-5.5 wins on Overall, Coding, Multimodal. Every numeric field is compared below, with a worked monthly-cost example and a pick rule for each use case.
Verdict at a glance
Choose GPT-5.5 if you…
- Balanced with no weak spot
- Richest ecosystem
- Mature plugin/function calling
- Strong creative writing
- Best for: General tasks, Creative writing, Coding
Choose DeepSeek-V4-Flash if you…
- Rock-bottom price
- Fast
- Open source
- Fit for simple tasks
- Best for: Ultra-fast response, Low cost, High concurrency
Head-to-head aggregate scores
Scores are 0–100, aggregated from public benchmark information and independently weighted across three leaderboards. Rank is out of 22 tracked models.
Aggregated from public sources and independently weighted; methodology on the Terms page. Scores within 3 points are treated as statistically tied.
Specs & pricing — every field side by side
List API prices in USD per 1M tokens. The highlighted cell is the stronger value/capability on that row.
| Dimension | GPT-5.5 | DeepSeek-V4-Flash | Verdict |
|---|---|---|---|
| Vendor | OpenAI (US) | DeepSeek (CN) | Different vendors |
| Released | 2026.04 | 2026.04 | DeepSeek-V4-Flash is newer |
| Overall (rank) | 81 · #5 | 67 · #16 | GPT-5.5 +14 |
| Coding | 75 · #8 | 65 · #16 | GPT-5.5 +10 |
| Multimodal | 85 · #8 | 65 · #20 | GPT-5.5 +20 |
| Context window | 1.05M | 1M | GPT-5.5 larger |
| Max output | 128K | 128K | Tie |
| Effective-context | 90 | 90 | Tie |
| Input $/1M | $5 | $0.14 | DeepSeek-V4-Flash cheaper |
| Output $/1M | $30 | $0.28 | DeepSeek-V4-Flash cheaper |
| Cache discount | 50% off | none | GPT-5.5 deeper |
| Speed | ~50 tok/s | ~85 tok/s | DeepSeek-V4-Flash faster |
| TTFT | 0.8s | 0.3s | DeepSeek-V4-Flash snappier |
| Function calling | 95 | 72 | GPT-5.5 ahead |
| Refusal rate | ~15% | ~5% | DeepSeek-V4-Flash less restrictive |
| English | 94 | 75 | GPT-5.5 |
| Chinese | 76 | 80 | DeepSeek-V4-Flash |
| Modalities | text, image | text | different coverage |
| Open weights | No | Yes | DeepSeek-V4-Flash is open |
| Fine-tuning | Yes | Yes | |
| Free tier | ChatGPT free tier available (rate-limited); Plus $20/month | DeepSeek App free | |
| SOC2 / no-train | yes / yes | no / yes | |
| Private deployment | No | Yes | DeepSeek-V4-Flash |
Fields drawn from vendor public documentation and the Modelspectra 22-model dataset; speed varies with network, concurrency and prompt length. Verify current pricing before purchase.
Dimension-by-dimension analysis
Reasoning & overall intelligence
GPT-5.5 leads the overall aggregate by 14 points (81 vs 67). That is a meaningful, not marginal, edge on hard, multi-step reasoning, while DeepSeek-V4-Flash remains a strong generalist that is not out of its depth on routine work.
Agentic coding
This is a clear gap: GPT-5.5 scores 75 against 65. On multi-file edits, SWE-style tickets and long-horizon agent loops GPT-5.5 needs fewer correction turns; DeepSeek-V4-Flash is still competent for scripts and assisted completion but trails as task complexity rises.
Multimodal
GPT-5.5 leads multimodal 85 vs 65. A concrete modality difference: GPT-5.5 additionally handles image. Neither emits native video, so the comparison is about parsing images and documents, not generation.
Speed & latency
DeepSeek-V4-Flash is faster in interactive use: ~85 tok/s with 0.3s TTFT versus ~50 tok/s with 0.8s TTFT (about 1.7× the throughput). For conversational UIs where perceived responsiveness drives retention, that edge is a real product factor even when raw reasoning is lower.
Context: window vs usable recall
Nominal windows are 1.05M for GPT-5.5 and 1M for DeepSeek-V4-Flash. Effective-context scores point the same way as window size — GPT-5.5 is ahead on usable recall (90 vs 90), so prefer it for long-document work where details cannot be missed.
Price & total cost
DeepSeek-V4-Flash is the cheaper API at $0.14/$0.28 versus GPT-5.5 at $5/$30 per 1M input/output tokens — list input is about 35.7× lower. Cache discounts (GPT-5.5 50%) shift the effective bill, worked out below.
Chinese vs English
English: GPT-5.5 94 vs DeepSeek-V4-Flash 75. Chinese: 76 vs 80. For Chinese-language production, DeepSeek-V4-Flash is the stronger pick. Note that non-Chinese models generally require overseas network access for their APIs.
Tool use & ecosystem
Function-calling score: GPT-5.5 95 vs DeepSeek-V4-Flash 72, so GPT-5.5 has the edge on structured tool use. Fine-tuning is available from GPT-5.5 and DeepSeek-V4-Flash. Factor in existing SDK/plugin familiarity — switching cost often outweighs a few-point tool-use gap.
Cost worked example — same workload, real token math
Assume a production workload of 100M input + 30M output tokens per month, with 90% of input tokens served from cache. Figures use public list prices.
| Scenario · per month | GPT-5.5 | DeepSeek-V4-Flash | Gap |
|---|---|---|---|
| List priceno cache applied | $1,400100M in × $5 + 30M out × $30 | $22100M in × $0.14 + 30M out × $0.28 | 63.64×gap |
| With caching90% of inputs cache-hit | $1,17590M cached in × $2.5 + 10M in × $5 + 30M out × $30 | $22no published cache discount | 53.41×gap |
Illustrative model; your input/output mix and cache-hit ratio change the result. Prices are list rates before any enterprise agreement.