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Qwen
qwen/qwen3.8-2.4t-a95bCatalogue: Indexed in the reference catalogue; nothing on this deployment answers as this model yet.
Published by the vendor; the platform bills at the target's declared price.
Qwen qwen/qwen3.8-2.4t-a95b
Qwen3.8 2.4T A95B is an open-weight sparse mixture-of-experts model from Qwen and the open-weight variant of [Qwen3.8 Max](/qwen/qwen3.8-max), with 95 billion active parameters out of 2.4 trillion total. It is...
Qwen3.8 2.4T A95B earns a request when it needs step-by-step reasoning, tool calls, very long inputs; a short, general request would go to MiniMax M3.1 Flash (free) instead - free per million input tokens against $2.00 here; and the hardest requests, where the quality floor rules it out, to Claude Opus 5.5 (batch). Your rules decide the floor; the trace shows the comparison for every request.
Lower input price and an intelligence index within 5 points.
Nothing on this deployment answers as this model yet. Connect your own provider under Model providers, or add a target to your catalogue - the router picks it up without retraining.
# targets.yaml - declare a target that runs Qwen3.8 2.4T A95B
targets:
- id: qwen3-8-2-4t-a95b
kind: llm
name: Qwen3.8 2.4T A95B
metadata:
model: qwen/qwen3.8-2.4t-a95b # links the target to this catalogue entry
capabilities:
domains: [general]
supports_tools: true
context_window: 1048576
cost:
usd_per_1k_tokens: 0.004000Input list price per million tokens; Qwen3.8 2.4T A95B is the 11th cheapest of 13 listed.
Photo: RDNE Stock project
Cached input reads $0.25 per 1M · weights on Hugging Face as Qwen/Qwen3.8-2.4T-A95B
A higher intelligence index, best first, with the price it comes at.
Other models by the same vendor in the catalogue.
The catalogue prints input and output prices and what three typical monthly workloads cost on each.