Models

claude-sonnet-5 vs qwen3.7-flash

Output tokens cost $10.00 per million on claude-sonnet-5 and $1.13 per million on qwen3.7-flash. Input tokens cost $2.00 per million on claude-sonnet-5 and $0.28 per million on qwen3.7-flash. Cached input tokens are billed at $2.00 per million on claude-sonnet-5 and $0.06 per million on qwen3.7-flash. Context windows are 1,000,000 tokens on claude-sonnet-5 and 991,000 tokens on qwen3.7-flash. First-token latency measured on AIHubMix is 3.3s on claude-sonnet-5 and 2.1s on qwen3.7-flash. Measured output throughput is 91.0 tokens/s on claude-sonnet-5 and 104.1 tokens/s on qwen3.7-flash.

Anthropicclaude-sonnet-5Qwenqwen3.7-flash
Anthropic
claude-sonnet-5
Anthropic · text, image → text

Claude Sonnet 5 is the next generation of Anthropic's Sonnet model family. It is a drop-in upgrade for Claude Sonnet 4.6 with three behavior changes: adaptive thinking is on by default, manual extended thinking now returns a 400 error (it was deprecated on Claude Sonnet 4.6), and setting sampling parameters (temperature, top_p, top_k) to non-default values returns a 400 error

Input$2.00 /M
Output$10.00 /M
Qwen
qwen3.7-flash
Qwen · text → text

The Qwen 3.7 series' mid-to-high cost-performance "Plus" model builds on strong text capabilities with a comprehensive upgrade to vision-language abilities, while retaining full agent capabilities in coding, tool use, and productivity workflows. Its core features are multimodal interactive hybrid agent capabilities, able to perceive real-world scenes, read screens and operate GUIs, generate code based on visual references, and provide end-to-end navigation of mobile applications.

Input$0.28 /M
Output$1.13 /M

Specs & Pricing

Prices are per million tokens. Latency and throughput are rolling averages measured on AIHubMix.

claude-sonnet-5
qwen3.7-flash
Input price
$2.00
$0.28
Output price
$10.00
$1.13
Cache read
$2.00
$0.06
Context window
1,000,000
991,000
Max output
128,000
64,000
Latency (first token)
3.3 s
2.1 s
Throughput
91.0 TPS
104.1 TPS
Modalities
textimage
text
Features
thinkingtoolsfunction callingstructured outputs
toolsfunction callingstructured outputsweblong contextthinking
Endpoints
chat_completions · gemini_api · claude_api

Promotional prices show the discounted rate; see each model page for promotion windows.

Usage on AIHubMix last 30 days

Daily traffic served through AIHubMix — how demand for each model is trending.

claude-sonnet-5qwen3.7-flash

Tokens / day

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Requests / day

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Live Performance last 3 days

Measured on real AIHubMix traffic, hourly buckets. Gaps mean no traffic in that hour.

claude-sonnet-5qwen3.7-flash

Throughput (TPS)

-

Latency (s)

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Uptime (%)

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Cost Calculator

Estimate your monthly bill for the same workload on each model.

qwen3.7-flash
$33.84 /mo
claude-sonnet-5
$270 /mo

Monthly = daily × 30. Discounted rates applied where a promotion is active.

FAQ

Which is cheaper: claude-sonnet-5, qwen3.7-flash?

qwen3.7-flash: $1.13/M output tokens; claude-sonnet-5: $10.00/M. Use the cost calculator above to estimate your own workload.

Which responds faster?

qwen3.7-flash: 2.1s first-token latency measured on AIHubMix; see the live performance charts above for how each model behaves across the day.

How large is each context window?

claude-sonnet-5 accepts 1,000,000 and qwen3.7-flash accepts 991,000 input tokens. Maximum output per request is 128,000 tokens on claude-sonnet-5 and 64,000 tokens on qwen3.7-flash.

Which one generates tokens faster?

qwen3.7-flash at 104.1 tokens/s and claude-sonnet-5 at 91.0 tokens/s, measured as output throughput on AIHubMix — a separate metric from first-token latency.

What inputs and capabilities does each model support?

claude-sonnet-5 accepts text and image input and supports thinking, tool calling, function calling and structured outputs; qwen3.7-flash accepts text input and supports tool calling, function calling, structured outputs, web search, long context and thinking.

Can I call claude-sonnet-5 and qwen3.7-flash with the same API key?

Yes. AIHubMix serves every model on this page behind one OpenAI-compatible endpoint, so switching between them is a one-line change to the model field — no second account, key or SDK.

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