DeepSeek-V4-Pro-Max: API Pricing, Context Window & Benchmarks
DeepSeek-V4-Pro-Max is a language model from DeepSeek, released in April 2026, with a 1.0M-token context window, and pricing from $1.74/M input and $3.48/M output.
DeepSeek-V4-Pro-Max is the maximum reasoning effort mode of DeepSeek-V4-Pro, a 1.6T-parameter MoE model with 49B activated parameters and a 1M-token context window. It introduces a hybrid attention architecture combining Compressed Sparse
DeepSeek-V4-Pro-Max benchmarks
Rankings
Quality Tracker
DeepSeek-V4-Pro-Max Performance Across Datasets
Scores sourced from the model's scorecard, paper, or official blog posts
llm-stats.com - Thu Jul 23 2026DeepSeek-V4-Pro-Max pricing
Providers
DeepSeek-V4-Pro-Max starts at $1.60 per million input tokens and $3.20 per million output tokens via Novita. See all 5 providers below with their per-token pricing, latency, throughput, and modality support.
| Provider | Input $/M | Output $/M | Context in / out | TTFT p50 / p95 s | Output avg / p5 c/s | Success 7d | Modalities in / out |
|---|---|---|---|---|---|---|---|
 Novita | $1.60 | $3.20 | 1.0M/131.1K | 2.20/6.36 | 113/3 | 83.33%(6) | / |
 DeepInfra | $1.74 | $3.48 | 1.0M/65.5K | 1.39/5.87 | 210/124 | 100.00%(20) | / |
 DeepSeek | $1.74 | $3.48 | 1.0M/393.2K | 1.13/3.94 | 159/38 | 75.00%(4) | / |
 Fireworks | $1.74 | $3.48 | 1.0M/65.5K | 2.32/12.87 | 172/9 | 66.67%(12) | / |
 Together | $1.74 | $3.48 | 524.3K/65.5K | 0.48/3.20 | 233/72 | 71.43%(7) | / |
Cached input is the discounted price for prompt tokens served from a provider cache. TTFT is time to first token. Output is characters per second; p5 is the sustained floor exceeded by 95% of observed requests. Success is calculated from completed versus failed requests over the trailing seven days.
DeepSeek-V4-Pro-Max model size
DeepSeek-V4-Pro-Max has 1.6 trillion parameters and was trained on 32 trillion tokens. See how it compares to other models in the same parameter range.
DeepSeek-V4-Pro-Max context window
Input and output token limits for DeepSeek-V4-Pro-Max, plus how it ranks on long-context understanding.
DeepSeek-V4-Pro-Max API
Run a request to see the response
Use it in your code
Billed at $1.74 input / $3.48 output per 1M tokens through the LLM Stats gateway.
from openai import OpenAI
client = OpenAI(
api_key="YOUR_API_KEY",
base_url="https://gateway.llm-stats.com/v1"
)
response = client.chat.completions.create(
model="deepseek-v4-pro-max",
messages=[
{"role": "user", "content": "What is machine learning?"}
]
)
print(response.choices[0].message.content)Need an API key? Create one above in the playground, or read the API documentation.
DeepSeek-V4-Pro-Max latency
DeepSeek-V4-Pro-Max time to first token, sustained output throughput, and failed-request rate from live API traffic over the trailing 7 days.
Provider operational metrics
Time to first token, output throughput, and failed-request rate from live API traffic
DeepSeek-V4-Pro-Max examples
Recent arena outputs from DeepSeek-V4-Pro-Max, picked from the highest-ranked matchups.
DeepSeek-V4-Pro-Max license
DeepSeek-V4-Pro-Max is released under the MIT license, which permits commercial use, has 1.6T parameters.
- License
- MIT
- Commercial use allowed
- Parameters
- 1.6T
MIT License - allows commercial use
DeepSeek-V4-Pro-Max resources
Official sources for DeepSeek-V4-Pro-Max: api documentation, official playground, source repository, model weights.
DeepSeek-V4-Pro-Max vs other models
The most-compared alternatives to DeepSeek-V4-Pro-Max are Claude Opus 4.6, Gemini 3 Flash, Claude Opus 4.5. Open any pair side-by-side for benchmarks, pricing, context, and latency.
Models like DeepSeek-V4-Pro-Max
Models ranked just above and below DeepSeek-V4-Pro-Max by LLM Stats score.
FAQ
Common questions about DeepSeek-V4-Pro-Max.