Qwen Qwen 2.5 Coder 32B Instruct

OpenRouter chat

Qwen Qwen 2.5 Coder 32B Instruct is an OpenRouter chat model.It supports a 33,792-token context windowwith up to 33,792 output tokens.Input is priced at $0.180/M tokens and output at $0.180/M tokens. Route Qwen Qwen 2.5 Coder 32B Instruct 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 Qwen Qwen 2.5 Coder 32B Instruct spend

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

~3K in / ~400 out · 5K req/day
3,000
033,792
400
033,792
5,000
01,000,000
Per request
$0.000612
in $0.000540 · out $0.000072
Per day
$3.06
5,000 requests
Per month
$93.14
152,188 requests

Estimate uses $0.1800/M input · $0.1800/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 $0.180/M
Output $0.180/M

Limits

Context window
33,792 tokens
Max input
33,792 tokens
Max output
33,792 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

  • !high cost — input + output rates are in the top 88% of priced chat peers; consider a cheaper sibling for high-volume workloads
  • !limited context — 33,792-token window is in the bottom quartile; not ideal for long documents or large RAG
  • !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 Qwen Qwen 2.5 Coder 32B Instruct yet. Have one to contribute? Submit a source — citations help us prioritise.

Try it

Call Qwen Qwen 2.5 Coder 32B Instruct 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.
# Qwen Qwen 2.5 Coder 32B Instruct 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="openrouter/qwen-qwen-2-5-coder-32b-instruct",
    messages=[{"role": "user", "content": "Hello, Qwen Qwen 2.5 Coder 32B Instruct!"}],
)

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="openrouter/qwen-qwen-2-5-coder-32b-instruct",
    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

Qwen Qwen 2.5 Coder 32B Instruct 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 Qwen Qwen 2.5 Coder 32B Instruct cost?

Input is priced at $0.180 per 1M tokens and output at $0.180 per 1M tokens (OpenRouter, last verified May 12, 2026).

What is the context window of Qwen Qwen 2.5 Coder 32B Instruct?

Qwen Qwen 2.5 Coder 32B Instruct supports a 33,792-token context window with up to 33,792 output tokens.

Does Qwen Qwen 2.5 Coder 32B Instruct support function calling?

Qwen Qwen 2.5 Coder 32B Instruct 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 Qwen Qwen 2.5 Coder 32B Instruct good for production?

Qwen Qwen 2.5 Coder 32B Instruct 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 Qwen Qwen 2.5 Coder 32B Instruct 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 Qwen Qwen 2.5 Coder 32B Instruct

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