Requesty

deepseek-v4-flash-vision-exp

Fireworks AI/🇺🇸 US/chat

DeepSeek V4 Flash Vision Exp is the first experimental multimodal model in the DeepSeek V4 family. It builds on DeepSeek V4 Flash with added visual modules and continued training for visual understanding, with substantially improved multimodal agent capabilities while remaining comparable on text only agent tasks. 305B MoE, 1M token context. Served via Fireworks.More
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Which id to call

fireworks/deepseek-v4-flash-vision-exp

This exact deployment on Fireworks AI, with no routing and no failover. Send it as the model field.

Input /1M

$0.22

$0.0070 cached

Output /1M

$0.66

3.0x input

Context

1.0M

131K output

Added

Aug 2026

chat

Capabilities 5/8

VisionReasoningTool callingCachingWeb searchJSON schemaComputer useImage generation

Provider rates

What deepseek-v4-flash-vision-exp costs

Provider prices per 1M tokens, updated September 8, 2026.more

These are the upstream provider rates. Pay as you go adds 5%, or 0% if you bring your own keys, and there is no per-request fee. Prompt caching and routing change what you pay against these rates, not the rates themselves.

Input /1M

$0.22

Output /1M

$0.66

Cache write /1M

-

Cache read /1M

$0.0070

What a workload costs

100K input + 10K output
$0.0286
1M input + 100K output
$0.29
10M input + 1M output
$2.86

At the rates above, before caching. A cache read costs $0.0070 per 1M, so repeated context lands under these figures.

OpenAI compatible

Call it in three lines

Change the base url, use your Requesty key, set the model to fireworks/deepseek-v4-flash-vision-exp. Existing OpenAI SDK code needs no other edit.

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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-flash-vision-exp",
    messages=[
        {"role": "user", "content": "Explain quantum computing in one paragraph."},
    ],
)

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

Reference

Specs and data terms

What the catalog reports for this deployment, and what the provider does with the traffic.

Context window1.0M tokens
Max output131K tokens
API typechat
AddedAug 2026
Model id
Data retentionNone
Used for trainingNo
Served from🇺🇸 US
Privacy policyFireworks Privacy Policy →

Public leaderboards

Benchmark scores

Benchmarks measure the model, not this endpoint, so they are the same wherever these weights are served.

No benchmarks are published for this exact variant yet.

Region-specific deployments and highspeed tiers usually share scores with their base model. Try the base model page or the Fireworks AI models overview.

Same provider

More from Fireworks AI

Newest first, on the same provider and the same key.

glm-5.3-flash

1.0M ctx/$0.15/1M

glm-5.3

1.0M ctx/$1.40/1M

nemotron-lightning-3.5-30b-a3b

262K ctx/$0.05/1M

deepseek-v4-pro-0813

1M ctx/$1.32/1M

muse-glimmer-30b

131K ctx/$0.35/1M

qwen3.8-max

1M ctx/$2.00/1M

Reference

deepseek-v4-flash-vision-exp questions

How much does deepseek-v4-flash-vision-exp cost?

deepseek-v4-flash-vision-exp is priced at $0.22 per million input tokens and $0.66 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. Those are the upstream provider rates: pay as you go adds 5% on top, or 0% if you bring your own provider keys.

What is the context window of deepseek-v4-flash-vision-exp?

deepseek-v4-flash-vision-exp 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-vision-exp do?

deepseek-v4-flash-vision-exp supports vision input, 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-vision-exp 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-flash-vision-exp". The Quickstart above shows Python, JavaScript and cURL snippets.

Can I run deepseek-v4-flash-vision-exp through Requesty?

Yes. deepseek-v4-flash-vision-exp runs through Requesty's OpenAI-compatible API, served from Fireworks AI. You do not host the model yourself: point base_url at Requesty, set the model to "fireworks/deepseek-v4-flash-vision-exp", and requests are routed to the upstream provider with automatic failover. The same key gives you 600+ other models too.

Call deepseek-v4-flash-vision-exp through one endpoint

One key for this endpoint and 600+ other models. No markup on provider prices, automatic failover, caching built in.

All Fireworks AI models