Qwen3 235B A22B Instruct 2507 Tput

Together AI chat

Qwen3 235B A22B Instruct 2507 Tput is a Together AI chat model.It supports a 262,000-token context window.Input is priced at $0.200/M tokens and output at $6.00/M tokens. Capabilities include function calling. Route Qwen3 235B A22B Instruct 2507 Tput 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 Qwen3 235B A22B Instruct 2507 Tput spend

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

~3K in / ~400 out · 5K req/day
3,000
0262,000
400
016,000
5,000
01,000,000
Per request
$0.003000
in $0.000600 · out $0.002400
Per day
$15.00
5,000 requests
Per month
$457
152,188 requests

Estimate uses $0.2000/M input · $6.00/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 $0.200/M
Output $6.00/M
Blended (3:1 in:out) $1.65/M
Cross-model comparable price

Context & limits

Context window
262,000 tokens
Max input
262,000 tokens
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

Strengths & caveats — when to pick Qwen3 235B A22B Instruct 2507 Tput

Data-driven from Qwen3 235B A22B Instruct 2507 Tput's percentile within chat peers.

Where it's strong

  • +parallel tool calls — only 18% 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 Qwen3 235B A22B Instruct 2507 Tput yet. Have one to contribute? Submit a source — citations help us prioritise.

Try it

Call Qwen3 235B A22B Instruct 2507 Tput 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.
# Qwen3 235B A22B Instruct 2507 Tput 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-qwen3-235b-a22b-instruct-2507-tput",
    messages=[{"role": "user", "content": "Hello, Qwen3 235B A22B Instruct 2507 Tput!"}],
)

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-qwen3-235b-a22b-instruct-2507-tput",
    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 ↗

Explore similar models

Qwen3 235B A22B Instruct 2507 Tput doesn't have a public Arena ELO score yet, so we group by provider only — quality-tier comparisons need a benchmark. Side-by-side links appear where a comparison page exists; otherwise, open the model profile.

FAQ

How much does Qwen3 235B A22B Instruct 2507 Tput cost?

Input is priced at $0.200 per 1M tokens and output at $6.00 per 1M tokens (Together AI, last verified Aug 6, 2026).

What is the context window of Qwen3 235B A22B Instruct 2507 Tput?

Qwen3 235B A22B Instruct 2507 Tput supports a 262,000-token context window.

Does Qwen3 235B A22B Instruct 2507 Tput support function calling?

Yes — Qwen3 235B A22B Instruct 2507 Tput supports function (tool) calling, including parallel tool calls.

Is Qwen3 235B A22B Instruct 2507 Tput good for production?

Qwen3 235B A22B Instruct 2507 Tput is well-suited for parallel tool calls — only 18% of chat models on Future AGI advertise this.

How can I route to Qwen3 235B A22B Instruct 2507 Tput 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 Qwen3 235B A22B Instruct 2507 Tput

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