Qwen Qwen2.5 7B Instruct Turbo

Together AI chat

Qwen Qwen2.5 7B Instruct Turbo is a Together AI chat model. Capabilities include function calling. Route Qwen Qwen2.5 7B Instruct Turbo via Future AGI's Agent Command Center for unified observability, caching, and 15 routing strategies including cost-optimized fallback.

Pricing source: unknown Last verified: May 12, 2026 View source ↗
Pricing not yet public

We don't have verified per-token pricing for Qwen Qwen2.5 7B Instruct Turbo yet. If you have a source from Together AI's documentation, help us add it — your submission gets reviewed within 48 hours.

Pricing

Per-token rates, expressed in USD per 1M tokens. Verified May 12, 2026.

Input
Output

Limits

Context window
Max input
Max output
Modalities
text

Capabilities

  • Function calling ✓ supported
  • Parallel tool calls ✓ supported
  • 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 — not advertised

Where it's strong

  • +parallel tool calls — only 21% of chat models on Future AGI advertise this

Watch out for

  • No major caveats flagged from public spec.

Benchmarks pending

We haven't logged public benchmark scores for Qwen Qwen2.5 7B Instruct Turbo yet. Have one to contribute? Submit a source — citations help us prioritise.

Try it

Call Qwen Qwen2.5 7B Instruct Turbo 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 Qwen2.5 7B Instruct Turbo 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="together-ai/qwen-qwen2-5-7b-instruct-turbo",
    messages=[{"role": "user", "content": "Hello, Qwen Qwen2.5 7B Instruct Turbo!"}],
)

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="together-ai/qwen-qwen2-5-7b-instruct-turbo",
    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 Qwen2.5 7B Instruct Turbo 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 Qwen2.5 7B Instruct Turbo cost?

Public per-token pricing for Qwen Qwen2.5 7B Instruct Turbo is not yet published. Submit a source on this page to help us add it.

What is the context window of Qwen Qwen2.5 7B Instruct Turbo?

Context window for Qwen Qwen2.5 7B Instruct Turbo is not currently public.

Does Qwen Qwen2.5 7B Instruct Turbo support function calling?

Yes — Qwen Qwen2.5 7B Instruct Turbo supports function (tool) calling, including parallel tool calls.

Is Qwen Qwen2.5 7B Instruct Turbo good for production?

Qwen Qwen2.5 7B Instruct Turbo is well-suited for parallel tool calls — only 21% of chat models on Future AGI advertise this.

How can I route to Qwen Qwen2.5 7B Instruct Turbo 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 Qwen2.5 7B Instruct Turbo

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