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Fireworks AI

deepseek-v4-pro

DeepSeek V4 Pro is a flagship open source Mixture of Experts model designed for frontier reasoning, advanced coding, and long context intelligence at scale (up to 1M tokens). It introduces a hybrid attention architecture that dramatically improves long context efficiency while reducing KV and compute overhead, along with stability and training enhancements for deep multi step reasoning. It represents a top tier open source system for complex agentic workflows, high precision reasoning, and demanding production workloads.

ReasoningTool callingCaching
Try deepseek-v4-proCompareDocs

Specifications

Context window1M tokens
Max output131K tokens
API typechat
AddedApr 29, 2026
Model IDfireworks/deepseek-v4-pro
Data retentionNo
Used for trainingNo
Provider locationπŸ‡ΊπŸ‡Έ US
Privacy policyFireworks Privacy Policy→

Benchmarks

Released 2026-04-24
Coding Indexcoding
47.5%

Artificial Analysis Coding Index β€” a composite of coding evaluations including LiveCodeBench, SciCode and Terminal-Bench.

GPQA Diamondreasoning
88.8%

Graduate-level physics, chemistry & biology questions designed to resist Googling.

Intelligence Indexreasoning
51.5%

Artificial Analysis Intelligence Index β€” a composite of multiple evaluations measuring overall model capability.

Scores are sourced from official model cards, Artificial Analysis, and public leaderboards. Benchmarks measure specific skills and do not capture every aspect of model quality β€” always test on your own workload.

Pricing

Input / 1M
$1.74
Output / 1M
$3.48
Cache write
β€”
Cache read / 1M
$0.15
Estimated cost
100K input + 10K output$0.21
1M input + 100K output$2.09
10M input + 1M output$20.88

Requesty charges exactly what the upstream provider charges β€” no markup, no per-request fees. Prompt caching and smart routing can reduce effective cost by 30-80%.

Quickstart

Drop-in compatible with the OpenAI SDK. Change the base URL, swap in your Requesty API key, and set the model to fireworks/deepseek-v4-pro.

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from openai import OpenAI

client = OpenAI(
    api_key="YOUR_REQUESTY_API_KEY",
    base_url="https://router.requesty.ai/v1",
)

response = client.chat.completions.create(
    model="fireworks/deepseek-v4-pro",
    messages=[
        {"role": "user", "content": "Explain quantum computing in one paragraph."},
    ],
)

print(response.choices[0].message.content)

Other Fireworks AI models

gpt-oss-120b
131K ctx$0.15/1M
Coding 29
gpt-oss-20b
131K ctx$0.07/1M
Coding 19
deepseek-v4-flash
1M ctx$0.14/1M
Coding 39
qwen3.6-plus
131K ctx$0.50/1M
Coding 43
minimax-m2.7
197K ctx$0.30/1M
Coding 42
glm-5.1
202K ctx$1.40/1M
Coding 43

Frequently asked questions

How much does deepseek-v4-pro cost?
deepseek-v4-pro is priced at $1.74 per million input tokens and $3.48 per million output tokens when accessed via Requesty. Prompt caching is supported, which can cut effective input cost by up to 90% on repeated context. Requesty charges exactly what the upstream provider charges β€” we don't add markup.
What is the context window of deepseek-v4-pro?
deepseek-v4-pro has a context window of 1M tokens, with a maximum output of 131K tokens per response. That's roughly 1,333 words of input you can fit in a single prompt.
How does deepseek-v4-pro perform on benchmarks?
deepseek-v4-pro scores 96.2% on τ²-Bench, 88.8% on GPQA Diamond, 51.5% on Intelligence Index. See the full benchmark chart above for results across MMLU Pro, GPQA Diamond, SWE-Bench Verified, HumanEval, MATH, AIME, MMMU, and LiveBench.
What can deepseek-v4-pro do?
deepseek-v4-pro supports tool calling, extended reasoning, prompt caching. You can call it through any OpenAI-compatible client by pointing base_url to Requesty.
How do I use deepseek-v4-pro with the OpenAI SDK?
Install the OpenAI SDK, set base_url to "https://router.requesty.ai/v1", set your API key to your Requesty key, and set the model to "fireworks/deepseek-v4-pro". The Quickstart above shows Python, JavaScript and cURL snippets.

Access deepseek-v4-pro through Requesty

One API key, 400+ models, OpenAI-compatible. No markup on provider prices, automatic failover, and smart caching built-in.

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