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GPT-5.5 vs DeepSeek V4.1 Flash
A straight cost comparison of GPT-5.5 (OpenAI) and DeepSeek V4.1 Flash (DeepSeek), per 1,000,000 tokens, verified October 2026.
Rate-by-rate comparison
| Metric | GPT-5.5 | DeepSeek V4.1 Flash | Winner |
|---|---|---|---|
| Input / 1M | $5 | $0.30 | DeepSeek V4.1 Flash |
| Cached input / 1M | $0.50 | $0.006 | DeepSeek V4.1 Flash |
| Cache write / 1M | — | — | Tie |
| Output / 1M | $30 | $1.20 | DeepSeek V4.1 Flash |
| Context window | 1,050,000 | 1,100,000 | DeepSeek V4.1 Flash |
| Batch API | Yes | No | GPT-5.5 |
| Long-context tier | > 272,000 | None | — |
For per-token metrics, the lower number wins. For context window and batch support, the higher or broader option wins. A dash means the provider does not publish that rate: a missing cache-write fee means writes are not billed per token, while a missing cached-input rate means cache hits bill at the full input rate.
Blended cost: 1M input + 250K output
| Model | Blended cost | Difference |
|---|---|---|
| GPT-5.5 | $12.50 | +$11.90 |
| DeepSeek V4.1 Flash | $0.60 | Cheaper |
Ten workloads, two bills
The same two models, priced across ten workloads that differ only in their input:output ratio. Nothing else changes — no retries, no system prompt, no middleware.
| Workload | GPT-5.5 | DeepSeek V4.1 Flash | Winner |
|---|---|---|---|
| Classification 100K reqs · 500 in / 10 out | $280 | $16.20 | DeepSeek V4.1 Flash |
| Data extraction 10K reqs · 2K in / 200 out | $160 | $8.40 | DeepSeek V4.1 Flash |
| Support chat 1K reqs · 4K in / 600 out | $38 | $1.92 | DeepSeek V4.1 Flash |
| Code review 2K reqs · 8K in / 1.5K out | $170 | $8.40 | DeepSeek V4.1 Flash |
| Summarisation 1K reqs · 20K in / 1K out | $130 | $7.20 | DeepSeek V4.1 Flash |
| Agent loop 5K reqs · 12K in / 2K out | $600 | $30 | DeepSeek V4.1 Flash |
| Translation 500 reqs · 15K in / 15K out | $263 | $11.25 | DeepSeek V4.1 Flash |
| Long-document QA 200 reqs · 120K in / 800 out | $125 | $7.39 | DeepSeek V4.1 Flash |
| Cached RAG 1K reqs · 50K in (45K cached) / 1K out | $77.70 | $2.98 | DeepSeek V4.1 Flash |
| Nightly batch 10K reqs · 10K in / 2K out | $550 | $54 | DeepSeek V4.1 Flash |
GPT-5.5 wins 0 of 10, DeepSeek V4.1 Flash wins 10 of 10. The winner is set by the token mix, not by the headline rate.
Where the two bills cross over
DeepSeek V4.1 Flash is cheaper on both sides of the mix: $0.30 vs $5 per million input tokens, and $1.20 vs $30 per million output. No input:output ratio reverses that, so on price alone the other model never becomes the better choice — it has to win on context, latency or output quality.
Cost at four scales
The same support-chat workload (4K input, 600 output per request) at four monthly volumes.
| Requests / month | GPT-5.5 | DeepSeek V4.1 Flash | Difference |
|---|---|---|---|
| 100 | $3.80 | $0.192 | DeepSeek V4.1 Flash cheaper by $3.61 |
| 1,000 | $38 | $1.92 | DeepSeek V4.1 Flash cheaper by $36.08 |
| 10,000 | $380 | $19.20 | DeepSeek V4.1 Flash cheaper by $361 |
| 100,000 | $3,800 | $192 | DeepSeek V4.1 Flash cheaper by $3,608 |
What caching does to each bill
Caching only helps the part of the prompt that repeats. This is the support-chat workload (1,000 requests, 4,000 input tokens each) with an increasing share of that prompt served from a warm cache, written once on the first request.
| Cached share of the prompt | GPT-5.5 | DeepSeek V4.1 Flash | Winner |
|---|---|---|---|
| 0% | $38 | $1.92 | DeepSeek V4.1 Flash |
| 50% | $29.01 | $1.33 | DeepSeek V4.1 Flash |
| 80% | $23.61 | $0.98 | DeepSeek V4.1 Flash |
| 95% | $20.92 | $0.804 | DeepSeek V4.1 Flash |
Both models publish a cached-read rate, so the discount is comparable: GPT-5.5 reads cache at $0.50 per million, DeepSeek V4.1 Flash at $0.006.
Which one should you pick?
GPT-5.5 wins on none of the ten workloads above, while DeepSeek V4.1 Flash wins on classification, data extraction, support chat, code review, summarisation, agent loop, translation, long-document qa, cached rag, nightly batch.
Beyond price, the two differ on input rate ($5 vs $0.30); output rate ($30 vs $1.20); cached-input rate ($0.50 vs $0.006); context window (1,050,000 vs 1,100,000); batch support (yes vs no); long-context tier (yes, above 272,000 vs none).
Batch mode is available on GPT-5.5, which halves the nightly job. Both publish cached-input discounts, so a stable system prompt is worth caching on either.
FAQ
Is GPT-5.5 cheaper than DeepSeek V4.1 Flash?
On a blended 1M-input-plus-250K-output workload, DeepSeek V4.1 Flash is cheaper by 95% ($0.60 vs $12.50). The gap changes for cache-heavy prompts and for batch jobs, as the workload table shows.
Which handles longer prompts, GPT-5.5 or DeepSeek V4.1 Flash?
DeepSeek V4.1 Flash has the larger context window (1,100,000 vs 1,050,000 tokens). Watch the long-context threshold on GPT-5.5: rates rise once input passes it.
Do both models support prompt caching?
GPT-5.5 bills cached reads at $0.50 per 1M; DeepSeek V4.1 Flash at $0.006.
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