DeepSeek V4 Flash

Azure AI Foundry chat

DeepSeek V4 Flash is an Azure AI Foundry chat model.It supports a 1,000,000-token context windowwith up to 384,000 output tokens.Input is priced at $0.190/M tokens and output at $0.510/M tokens. Capabilities include function calling, reasoning. Route DeepSeek V4 Flash via Future AGI's Agent Command Center for unified observability, caching, and 15 routing strategies including cost-optimized fallback.

Pricing source: litellm Last verified: Aug 6, 2026 View source ↗
Cost calculator

Estimate DeepSeek V4 Flash spend

Pick a workload, fine-tune the sliders, and see the monthly bill.

~3K in / ~400 out · 5K req/day
3,000
01,000,000
400
0200,000
5,000
01,000,000
Per request
$0.000774
in $0.000570 · out $0.000204
Per day
$3.87
5,000 requests
Per month
$118
152,188 requests

Estimate uses $0.1900/M input · $0.5100/M output. Provider pricing changes. Production costs vary with retries, streaming overhead, and tool-call rounds.
Want this for free? Cache + route via Agent Command Center — first 100K requests and 100K cache hits free every month.

Pricing

Per-token rates, expressed in USD per 1M tokens. Verified Aug 6, 2026.

Input $0.190/M
Output $0.510/M
Blended (3:1 in:out) $0.270/M
Cross-model comparable price

Context & limits

Context window
1,000,000 tokens
Max input
1,000,000 tokens
Max output
384,000 tokens
Modalities
text

Capabilities

  • Function calling ✓ supported
  • Parallel tool calls — not advertised
  • Vision input — not advertised
  • Audio input — not advertised
  • Audio output — not advertised
  • PDF input — not advertised
  • Streaming ✓ supported
  • Structured output — not advertised
  • Prompt caching — not advertised
  • Reasoning ✓ supported

Strengths & caveats — when to pick DeepSeek V4 Flash

Data-driven from DeepSeek V4 Flash's percentile within chat peers.

Where it's strong

  • +long-context tasks — context window in the top 10% of peers
  • +long-form generation — 384,000-token max output, top-2% of peers

Watch out for

  • !strict structured output — no JSON-schema enforcement, expect retry loops

Benchmark scores

Reported public benchmark numbers. Each row links to the source. Faded bar shows 6-peer average for context.

Chatbot Arena ELOgeneral· overall
Captured Aug 8, 2026
Try it

Call DeepSeek V4 Flash via Agent Command Center

One OpenAI-compatible endpoint. Routing, fallback, semantic caching, guardrails, and cost tracking come along for the ride. First 100K requests + 100K cache hits free every month.

SDK
Native Future AGI client (agentcc / @agentcc/client). Per-call metadata — provider, cost, latency, cache hit, request id — is returned on x-agentcc-* response headers, so any HTTP client can read it.
# DeepSeek V4 Flash via the Agent Command Center Python SDK
# pip install agentcc
import os
from agentcc import AgentCC

client = AgentCC(
    api_key=os.environ["AGENTCC_API_KEY"],   # from app.futureagi.com → Settings → API Keys
    base_url="https://gateway.futureagi.com/v1",
)

resp = client.chat.completions.create(
    model="azure-ai-foundry/deepseek-v4-flash",
    messages=[{"role": "user", "content": "Hello, DeepSeek V4 Flash!"}],
)

print(resp.choices[0].message.content)
print(f"Tokens: {resp.usage.total_tokens}")

# Per-call gateway metadata is returned on x-agentcc-* response headers.
# When you need it programmatically, use .with_raw_response to get them:
raw = client.chat.completions.with_raw_response.create(
    model="azure-ai-foundry/deepseek-v4-flash",
    messages=[{"role": "user", "content": "Same call, but I want the headers."}],
)
print("Provider:", raw.headers.get("x-agentcc-provider"))
print("Latency:", raw.headers.get("x-agentcc-latency-ms"), "ms")
print("Cost:   ", raw.headers.get("x-agentcc-cost"), "USD")
print("Cache:  ", raw.headers.get("x-agentcc-cache"))
Set AGENTCC_API_KEY with a key fromapp.futureagi.com.Gateway docs ↗
Advanced: fallback + cache config (YAML)
strategy: cost-optimized
targets:
  - model: deepseek-v4-flash
    provider: azure-ai-foundry
    weight: 80
fallbacks:
  - model: qwen3-8-max
    provider: dashscope
  - model: gemini-3-1-pro-preview
    provider: google
guardrails: [pii, prompt-injection, secrets]
cache: { exact: true, semantic: true }

Same model on other providers

deepseek-v4-flash is also available via 2 other routes. Pricing, regions, and capabilities can differ — compare before routing production traffic.

ProviderInput / 1MOutput / 1MVerified
Fireworks AI$0.140/M$0.280/MAug 6, 2026
DeepSeek$0.140/M$0.280/MAug 6, 2026

Compare with similar models

Grouped by Chatbot Arena tier (DeepSeek V4 Flash sits at 1436 ELO).

FAQ

How much does DeepSeek V4 Flash cost?

Input is priced at $0.190 per 1M tokens and output at $0.510 per 1M tokens (Azure AI Foundry, last verified Aug 6, 2026).

What is the context window of DeepSeek V4 Flash?

DeepSeek V4 Flash supports a 1,000,000-token context window with up to 384,000 output tokens.

Does DeepSeek V4 Flash support function calling?

Yes — DeepSeek V4 Flash supports function (tool) calling.

Is DeepSeek V4 Flash good for production?

DeepSeek V4 Flash is well-suited for long-context tasks — context window in the top 10% of peers and long-form generation — 384,000-token max output, top-2% of peers. Consider alternatives if you need strict structured output — no JSON-schema enforcement, expect retry loops.

How can I route to DeepSeek V4 Flash with fallback?

Use Agent Command Center: a single OpenAI-compatible endpoint that supports cost-optimized routing, latency-aware retries, model fallback, and shadow traffic. Configure once, swap models without app changes.

Useful links for DeepSeek V4 Flash

Official sources, independent benchmarks, and pricing aggregators — no random search-engine guesses.