DeepSeek V4--性能几乎达到前沿水平,价格却仅为其一小部分
Simon Willison 实测结论很直白,DeepSeek V4 性能几乎摸到前沿,价格却便宜一个量级,对预算卡死的团队是重大利好。
DeepSeek发布了V4版本模型,其性能已接近行业最前沿水平,但在价格上具有显著优势,仅为主要竞争对手的一小部分。该模型在多项基准测试中表现出色,能以极低的成本提供顶级的AI能力,有望大幅降低企业和开发者的使用门槛,推动AI技术的更广泛普及。
DeepSeek V4—almost on the frontier, a fraction of the price
24th April 2026
Chinese AI lab DeepSeek’s last model release was V3.2 (and V3.2 Speciale) last December. They just dropped the first of their hotly anticipated V4 series in the shape of two preview models, DeepSeek-V4-Pro and DeepSeek-V4-Flash.
Both models are 1 million token context Mixture of Experts. Pro is 1.6T total parameters, 49B active. Flash is 284B total, 13B active. They’re using the standard MIT license.
I think this makes DeepSeek-V4-Pro the new largest open weights model. It’s larger than Kimi K2.6 (1.1T) and GLM-5.1 (754B) and more than twice the size of DeepSeek V3.2 (685B).
Pro is 865GB on Hugging Face, Flash is 160GB. I’m hoping that a lightly quantized Flash will run on my 128GB M5 MacBook Pro. It’s possible the Pro model may run on it if I can stream just the necessary active experts from disk.
For the moment I tried the models out via OpenRouter, using llm-openrouter:
llm install llm-openrouter
llm openrouter refresh
llm -m openrouter/deepseek/deepseek-v4-pro 'Generate an SVG of a pelican riding a bicycle'
Here’s the pelican for DeepSeek-V4-Flash:

And for DeepSeek-V4-Pro:

For comparison, take a look at the pelicans I got from DeepSeek V3.2 in December, V3.1 in August, and V3-0324 in March 2025.
So the pelicans are pretty good, but what’s really notable here is the cost. DeepSeek V4 is a very, very inexpensive model.
This is DeepSeek’s pricing page. They’re charging $0.14/million tokens input and $0.28/million tokens output for Flash, and $1.74/million input and $3.48/million output for Pro.
Here’s a comparison table with the frontier models from Gemini, OpenAI and Anthropic:
| Model | Input ($/M) | Output ($/M) |
|---|---|---|
| DeepSeek V4 Flash | $0.14 | $0.28 |
| GPT-5.4 Nano | $0.20 | $1.25 |
| Gemini 3.1 Flash-Lite | $0.25 | $1.50 |
| Gemini 3 Flash Preview | $0.50 | $3 |
| GPT-5.4 Mini | $0.75 | $4.50 |
| Claude Haiku 4.5 | $1 | $5 |
| DeepSeek V4 Pro | $1.74 | $3.48 |
| Gemini 3.1 Pro | $2 | $12 |
| GPT-5.4 | $2.50 | $15 |
| Claude Sonnet 4.6 | $3 | $15 |
| Claude Opus 4.7 | $5 | $25 |
| GPT-5.5 | $5 | $30 |
DeepSeek-V4-Flash is the cheapest of the small models, beating even OpenAI’s GPT-5.4 Nano. DeepSeek-V4-Pro is the cheapest of the larger frontier models.
This note from the DeepSeek paper helps explain why they can price these models so low—they’ve focused a great deal on efficiency with this release, especially for longer context prompts:
In the scenario of 1M-token context, even DeepSeek-V4-Pro, which has a larger number of activated parameters, attains only 27% of the single-token FLOPs (measured in equivalent FP8 FLOPs) and 10% of the KV cache size relative to DeepSeek-V3.2. Furthermore, DeepSeek-V4-Flash, with its smaller number of activated parameters, pushes efficiency even further: in the 1M-token context setting, it achieves only 10% of the single-token FLOPs and 7% of the KV cache size compared with DeepSeek-V3.2.
DeepSeek’s self-reported benchmarks in their paper show their Pro model competitive with those other frontier models, albeit with this note:
Through the expansion of reasoning tokens, DeepSeek-V4-Pro-Max demonstrates superior performance relative to GPT-5.2 and Gemini-3.0-Pro on standard reasoning benchmarks. Nevertheless, its performance falls marginally short of GPT-5.4 and Gemini-3.1-Pro, suggesting a developmental trajectory that trails state-of-the-art frontier models by approximately 3 to 6 months.
I’m keeping an eye on huggingface.co/unsloth/models as I expect the Unsloth team will have a set of quantized versions out pretty soon. It’s going to be very interesting to see how well that Flash model runs on my own machine.
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This is DeepSeek V4—almost on the frontier, a fraction of the price by Simon Willison, posted on 24th April 2026.
ai 2,073 generative-ai 1,830 llms 1,798 llm 606 llm-pricing 77 pelican-riding-a-bicycle 118 deepseek 33 llm-release 205 openrouter 26 ai-in-china 95Next: Tracking the history of the now-deceased OpenAI Microsoft AGI clause
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