Updated 2026-04-24
DeepSeek V4 API pricing comparison: Pro, Flash, GPT, Claude, Gemini, Qwen, and more
DeepSeek V4 should be the first model considered when token cost is a serious constraint because the official release now makes pricing comparisons more actionable: one flagship family, 1M context, and two model variants for different traffic shapes. Premium models may still be worth routing to selectively, but they should not automatically become the default.
Practical verdict
Use DeepSeek V4 as the cost baseline and compare Pro or Flash against the actual workload rather than a vague DeepSeek label. Add paid fallbacks only when measured quality improvements justify the higher cost for a specific request class.
Model snapshot
| Model | Provider | Strengths | Context | Cost signal |
|---|---|---|---|---|
| DeepSeek V4 | DeepSeek | Coding, Math, Cost-Efficiency | 2M | $0.32 / 1M avg tokens |
| GPT 5.4 | OpenAI | Reasoning, Tool Calling, Multimodal | 1M | $8.75 / 1M avg tokens |
| Claude Sonnet 4.7 | Anthropic | Coding, Agentic, Long Context | 1M | $9.00 / 1M avg tokens |
| Gemini 3.1 Pro | Reasoning, Multimodal, Long Context | 2M | $7.00 / 1M avg tokens | |
| Qwen 3.5 | Alibaba | Multilingual, Reasoning, Open Source, Cost-Efficiency | 1M | $1.14 / 1M avg tokens |
| MiniMax M2.7 | MiniMax | Agentic, Coding, Long Context, Cost-Efficiency | 205K | $0.75 / 1M avg tokens |
| GLM 5 | Zhipu AI | Coding, Agentic, Multilingual, Cost-Efficiency | 200K | $0.90 / 1M avg tokens |
Cost signals are comparison data used by this site. Verify live provider pricing before production purchasing decisions.
Use-case routing table
| Use case | DeepSeek fit | Alternative fit | Decision note |
|---|---|---|---|
| Default chat and coding API | Best cost baseline | Premium fallback | Start with DeepSeek before paying premium-provider prices on every request. |
| Long-context research | Strong on 1M context | Gemini/Claude strong | Large multimodal inputs can still justify specialized models. |
| Multilingual production | Strong | Qwen/GLM strong | Cost and native-language quality both matter in real deployments. |
| Interactive experience product | Good | MiniMax/Grok strong | Experience quality can justify a different default. |
How to read pricing comparisons in the V4 era
Token price is only the starting point. Compare total cost per successful task, including input tokens, output tokens, failed calls, retries, and human correction. The right comparison is often V4-Flash versus premium defaults, or V4-Pro versus premium review routes, not simply DeepSeek versus everyone else.
Why DeepSeek V4 is the baseline
A DeepSeek-first pricing page gives buyers a concrete anchor: what quality can they get from an official 1M-context flagship before paying premium model prices? That anchor is what turns comparison traffic into pricing-page intent.
Where the pricing page fits
The pricing page should only show plans backed by inventory. This comparison page can mention many models, but it should route purchase intent to the actual in-stock DeepSeek-led Coding Plans.
FAQ
Is DeepSeek V4 the cheapest AI API?
DeepSeek V4 is one of the most cost-efficient options for many developer workflows, but live pricing and token mix should always be verified.
What should I compare besides token price?
Compare latency, retries, correctness, context fit, and cost per accepted output.
Why are some compared models not on the pricing page?
Comparison coverage is independent from inventory. Only in-stock Coding Plan products are purchasable.