Requesty
sference

deepseek-v4-flash-0731

DeepSeek V4 Flash is an efficiency-focused MoE model with 284B total parameters (13B active) and a 1M-token context window. It's tuned for fast inference and high-throughput use cases while still holding up on reasoning and coding tasks.

ReasoningTool callingCachingJSON schema
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Specifications

Context window1.0M tokens
Max output131K tokens
API typechat
AddedJul 31, 2026
Model ID
Data retentionNo
Used for trainingNo
Provider location🇪🇺 EU
Privacy policysference Privacy Policy→

Benchmarks

Benchmarks haven't been published yet for this exact variant.

Some variants (region-specific deployments, highspeed tiers) share benchmarks with their base model. Check the base model page or the sference models overview.

Pricing

Prices updated August 3, 2026
Input / 1M
$0.14
Output / 1M
$0.28
Cache write
N/A
Cache read / 1M
$0.07
Estimated cost
100K input + 10K output$0.0168
1M input + 100K output$0.17
10M input + 1M output$1.68

Requesty charges exactly what the upstream provider charges, 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 sference/deepseek-v4-flash-0731.

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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="sference/deepseek-v4-flash-0731",
    messages=[
        {"role": "user", "content": "Explain quantum computing in one paragraph."},
    ],
)

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

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Frequently asked questions

How much does deepseek-v4-flash-0731 cost?
deepseek-v4-flash-0731 is priced at $0.14 per million input tokens and $0.28 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, we don't add markup.
What is the context window of deepseek-v4-flash-0731?
deepseek-v4-flash-0731 has a context window of 1.0M tokens, with a maximum output of 131K tokens per response. That's roughly 1,398 words of input you can fit in a single prompt.
What can deepseek-v4-flash-0731 do?
deepseek-v4-flash-0731 supports tool calling, extended reasoning, prompt caching, structured outputs (JSON schema). You can call it through any OpenAI-compatible client by pointing base_url to Requesty.
How do I use deepseek-v4-flash-0731 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 "sference/deepseek-v4-flash-0731". The Quickstart above shows Python, JavaScript and cURL snippets.
Can I run deepseek-v4-flash-0731 through Requesty?
Yes. deepseek-v4-flash-0731 runs through Requesty's OpenAI-compatible API, served from sference. You do not host the model yourself: point base_url at Requesty, set the model to "sference/deepseek-v4-flash-0731", and requests are routed to the upstream provider with automatic failover. The same key gives you 600+ other models too.

Access deepseek-v4-flash-0731 through Requesty

One API key, 600+ models, OpenAI-compatible. No markup on provider prices, automatic failover, and smart caching built-in.

All sference models