Accounts Fireworks Models Qwen2p5 Coder 32B Instruct 64k

Fireworks AI chat

Accounts Fireworks Models Qwen2p5 Coder 32B Instruct 64k is a Fireworks AI chat model.It supports a 65,536-token context windowwith up to 65,536 output tokens.Input is priced at $0.900/M tokens and output at $0.900/M tokens. Route Accounts Fireworks Models Qwen2p5 Coder 32B Instruct 64k via Future AGI's Agent Command Center for unified observability, caching, and 15 routing strategies including cost-optimized fallback.

Pricing source: litellm Last verified: May 12, 2026 View source ↗
Cost calculator

Estimate Accounts Fireworks Models Qwen2p5 Coder 32B Instruct 64k spend

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

~3K in / ~400 out · 5K req/day
3,000
065,536
400
065,536
5,000
01,000,000
Per request
$0.003060
in $0.002700 · out $0.000360
Per day
$15.30
5,000 requests
Per month
$466
152,188 requests

Estimate uses $0.9000/M input · $0.9000/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 May 12, 2026.

Input $0.900/M
Output $0.900/M

Limits

Context window
65,536 tokens
Max input
65,536 tokens
Max output
65,536 tokens
Modalities
text

Capabilities

  • Function calling — not advertised
  • 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 — not advertised

Where it's strong

Watch out for

  • !agentic workflows — no advertised function-calling; use a tool-capable model and route via Agent Command Center for fallback
  • !strict structured output — no JSON-schema enforcement, expect retry loops

Benchmarks pending

We haven't logged public benchmark scores for Accounts Fireworks Models Qwen2p5 Coder 32B Instruct 64k yet. Have one to contribute? Submit a source — citations help us prioritise.

Try it

Call Accounts Fireworks Models Qwen2p5 Coder 32B Instruct 64k 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.
# Accounts Fireworks Models Qwen2p5 Coder 32B Instruct 64k 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/accounts-fireworks-models-qwen2p5-coder-32b-instruct-64k",
    messages=[{"role": "user", "content": "Hello, Accounts Fireworks Models Qwen2p5 Coder 32B Instruct 64k!"}],
)

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/accounts-fireworks-models-qwen2p5-coder-32b-instruct-64k",
    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 ↗

Compare with similar models

Accounts Fireworks Models Qwen2p5 Coder 32B Instruct 64k doesn't have a public Arena ELO score yet, so we group by provider only — quality-tier comparisons need a benchmark.

FAQ

How much does Accounts Fireworks Models Qwen2p5 Coder 32B Instruct 64k cost?

Input is priced at $0.900 per 1M tokens and output at $0.900 per 1M tokens (Fireworks AI, last verified May 12, 2026).

What is the context window of Accounts Fireworks Models Qwen2p5 Coder 32B Instruct 64k?

Accounts Fireworks Models Qwen2p5 Coder 32B Instruct 64k supports a 65,536-token context window with up to 65,536 output tokens.

Does Accounts Fireworks Models Qwen2p5 Coder 32B Instruct 64k support function calling?

Accounts Fireworks Models Qwen2p5 Coder 32B Instruct 64k does not currently advertise function-calling support. For agentic workloads, prefer a tool-calling-capable model and route via Agent Command Center for fallback.

Is Accounts Fireworks Models Qwen2p5 Coder 32B Instruct 64k good for production?

Accounts Fireworks Models Qwen2p5 Coder 32B Instruct 64k is best evaluated against your own production traces. Pipe traffic through Agent Command Center to compare it head-to-head against alternatives in shadow mode.

How can I route to Accounts Fireworks Models Qwen2p5 Coder 32B Instruct 64k 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 Accounts Fireworks Models Qwen2p5 Coder 32B Instruct 64k

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