AI model comparison
DeepSeek V4.1 Flash vs o3 Pro
Side by side comparison of DeepSeek V4.1 Flash and o3 Pro on pricing, benchmark scores, context window, and more.
DeepSeek V4.1 Flash is a sparse mixture-of-experts model from DeepSeek, and the first built on the company's Causal Encoder-Decoder (CED) architecture.
- Input / 1M
- $0.30
- Output / 1M
- $1.20
- Context
- 1.05M
The o-series of models are trained with reinforcement learning to think before they answer and perform complex reasoning.
- Input / 1M
- $20
- Output / 1M
- $80
- Context
- 200K
Comparing image generators? Compare image models
At a glance
Quick verdict
How the two models stack up on the things people ask about most.
Lower price
DeepSeek V4.1 Flash
66.7x cheaper for a typical chat
Higher intelligence score
DeepSeek V4.1 Flash
24.7 vs 21.9 on Artificial Analysis
Larger context window
DeepSeek V4.1 Flash
1.05M vs 200K tokens
Newer release
DeepSeek V4.1 Flash
Released September 10, 2026
Benchmarks
Benchmark scores
Independent scores from Artificial Analysis. Higher is better.
Intelligence index
Coding index
Agentic index
Pricing
DeepSeek V4.1 Flash vs o3 Pro API pricing
Per-token API rates. Cheaper option highlighted.
| Metric | ||
|---|---|---|
| Input tokensPer 1M tokens | $0.30 | $20 |
| Output tokensPer 1M tokens | $1.20 | $80 |
| Cached input (read)Per 1M tokens | $0.01 | Not available |
| Cache writePer 1M tokens | Not available | Not available |
| Web searchPer request | Not available | $0.01 |
What it costs in practice
Estimated cost per 1,000 requests at standard rates. Coding and long-document figures also show the cost when the input is already cached.
Chat message
2K in, 500 out
Coding task
30K in, 4K out
Long document summary
150K in, 2K out
Specs
Context window and capabilities
How much each model can read, how much it can write, and what it accepts as input.
| Metric | ||
|---|---|---|
| Context window | 1.05M tokens | 200K tokens |
| Max output | 944K tokens | 100K tokens |
| Input types | Image, Text | File, Image, Text |
| Output types | Text | Text |
| Reasoning effort levels | Max, High, Low, None | Not available |
| Default reasoning effort | High | Not available |
| Release date | September 10, 2026 | June 10, 2025 |
Features
Supported features
API features available for each model.
| Metric | ||
|---|---|---|
| Tool calling | Supported | Supported |
| Structured outputs | Supported | Supported |
| JSON mode | Supported | Supported |
| Reasoning | Supported | Supported |
| Temperature | Supported | Not supported |
| Stop sequences | Supported | Not supported |
| Deterministic seed | Supported | Supported |
| Verbosity control | Not supported | Not supported |
Our take
DeepSeek V4.1 Flash is 66.7x cheaper for a typical chat. DeepSeek V4.1 Flash scores higher on the Artificial Analysis Intelligence Index (24.7 vs 21.9). DeepSeek V4.1 Flash has the larger context window (1.05M vs 200K tokens). The right pick depends on your workload, so the quickest way to settle it is to send the same prompt to both and compare.
FAQ
Frequently asked questions
Is DeepSeek V4.1 Flash or o3 Pro cheaper?
DeepSeek V4.1 Flash is cheaper for a typical chat (2K input tokens and 500 output tokens). DeepSeek V4.1 Flash costs $0.30 per 1M input tokens and $1.20 per 1M output tokens, while o3 Pro costs $20 per 1M input tokens and $80 per 1M output tokens.
Which has a bigger context window, DeepSeek V4.1 Flash or o3 Pro?
DeepSeek V4.1 Flash supports up to 1.05M tokens of context, compared with 200K for o3 Pro.
Is DeepSeek V4.1 Flash smarter than o3 Pro?
On the Artificial Analysis Intelligence Index, DeepSeek V4.1 Flash scores 24.7 and o3 Pro scores 21.9, putting DeepSeek V4.1 Flash ahead. Benchmarks don't capture everything, so the best test is running your own prompts through both.
Can I use DeepSeek V4.1 Flash and o3 Pro at the same time?
Yes. Shortcut Chat sends one prompt to multiple models at once, so you can see DeepSeek V4.1 Flash and o3 Pro answer side by side and keep the better response.
Why choose? Ask both.
Send one prompt to DeepSeek V4.1 Flash and o3 Pro at the same time. Compare the answers side by side and keep the best one.