DeepSeek V4 Pro

Fireworks AI chat

DeepSeek V4 Pro is a Fireworks AI chat model.It supports a 1,048,576-token context windowwith up to 384,000 output tokens.Input is priced at $1.74/M tokens and output at $3.48/M tokens. Capabilities include function calling, reasoning. Route DeepSeek V4 Pro 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 Pro spend

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

~3K in / ~400 out · 5K req/day
3,000
01,048,576
400
0200,000
5,000
01,000,000
cached @ $0.1450/M
Per request
$0.006612
in $0.005220 · out $0.001392
Per day
$33.06
5,000 requests
Per month
$1,006
152,188 requests

Estimate uses $1.74/M input · $3.48/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 $1.74/M
Output $3.48/M
Blended (3:1 in:out) $2.18/M
Cross-model comparable price
Cached input $0.145/M

Context & limits

Context window
1,048,576 tokens
Max input
1,048,576 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 ✓ supported
  • Prompt caching — not advertised
  • Reasoning ✓ supported

Strengths & caveats — when to pick DeepSeek V4 Pro

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

Where it's strong

  • +long-context tasks — context window in the top 3% of peers
  • +long-form generation — 384,000-token max output, top-2% of peers

Watch out for

  • No major caveats flagged from public spec.

Benchmark scores

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

Chatbot Arena ELOgeneral· overall↓0% vs peers
Captured Aug 8, 2026
Try it

Call DeepSeek V4 Pro 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 Pro 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="fireworks-ai/deepseek-v4-pro",
    messages=[{"role": "user", "content": "Hello, DeepSeek V4 Pro!"}],
)

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="fireworks-ai/deepseek-v4-pro",
    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-pro
    provider: fireworks-ai
    weight: 80
fallbacks:
  - model: claude-fable-5
    provider: azure-ai-foundry
  - model: claude-opus-4-6
    provider: azure-ai-foundry
guardrails: [pii, prompt-injection, secrets]
cache: { exact: true, semantic: true }

Same model on other providers

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

ProviderInput / 1MOutput / 1MVerified
Azure AI Foundry$1.74/M$3.48/MAug 6, 2026
DeepSeek$0.435/M$0.870/MAug 6, 2026

Compare with similar models

Grouped by Chatbot Arena tier (DeepSeek V4 Pro sits at 1458 ELO).

FAQ

How much does DeepSeek V4 Pro cost?

Input is priced at $1.74 per 1M tokens and output at $3.48 per 1M tokens (Fireworks AI, last verified Aug 6, 2026).

What is the context window of DeepSeek V4 Pro?

DeepSeek V4 Pro supports a 1,048,576-token context window with up to 384,000 output tokens.

Does DeepSeek V4 Pro support function calling?

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

Is DeepSeek V4 Pro good for production?

DeepSeek V4 Pro is well-suited for long-context tasks — context window in the top 3% of peers and long-form generation — 384,000-token max output, top-2% of peers.

How can I route to DeepSeek V4 Pro 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 Pro

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