Alibaba Qwen: Qwen3.8 2.4T A95B

Qwen3.8 2.4T A95B is Alibaba Qwen's open-weight mixture-of-experts model, released 2026-08, with 95 billion active parameters out of 2.4 trillion total. It is the open-weight variant of Qwen3.8 Max and is suited for coding, research, complex reasoning, and agentic workflows.

Modalities
inTextoutText
Price / 1M−10%
$1.80 / $5.40$2.00 / $6.00
Context
1.049M
Released
Aug 12, 2026

Channels

Every channel serves the same model, but they differ in price and stability. On each API key in the Platform, you pick a primary and a backup channel per vendor, and each billing line shows which channel served the request.

Provider
Discount
Input /M
Output /M
Cache read /M
Cache write 5m /M
Cache write 1h /M
Defaultstable
−10%
$1.80
$5.40
$0.45
—
—

Capabilities

ReasoningTool useLong contextPrompt cachingStructured output

Parameters

Request parameters this model accepts through the API.

frequency_penaltyinclude_reasoninglogit_biaslogprobsmax_tokensmin_ppresence_penaltyreasoningreasoning_effortrepetition_penaltyresponse_formatseedstopstructured_outputstemperaturetool_choicetoolstop_ktop_logprobstop_p

Cost calculator

Pick a channel and a usage scenario, then drag the sliders to match your workload. Each scenario assumes a different prompt-cache hit rate.

Channel
Scenario
Unit $1.80 / $5.40 /1MDaily chat: 40% cache hit rate assumed · cache read $0.45 /1M
List price $422.40On MirAPI$380.16/ moYou save $42.24Create an API key

Benchmarks

bar = score (0–100) · ▏ median

Scores come from vendor reports and public leaderboards, not private evals.

Intelligence Index
General ability
39.9
#22
Coding Index
Code
71.9
#16
Agentic Index
Agentic
50.1
#10
GPQA Diamond
Science QA
87.1
#42
τ-bench (airline)
Agentic tool use
75.6
#27

Showcase

Every chat model gets the same three fixed prompts. Outputs are archived verbatim, so you can copy a prompt and reproduce the result.

Task prompt · identical for all models
Build a single-file HTML page using three.js from a CDN: a low-poly planet with a tilted ring of ~200 orbiting particles, a soft key light plus rim light, slow auto-rotation, and drag-to-orbit controls. No build tools — one file only.
Archived output
Archive not published yet

Every model will run this exact prompt, and its output will appear here verbatim with token counts and the cost per run.

Quick start

import os
from openai import OpenAI

client = OpenAI(
    base_url="https://api.mirapi.ai/v1",   # changed
    api_key=os.environ["MIRAPI_API_KEY"],   # changed
)

resp = client.chat.completions.create(
    model="qwen3.8-2.4t-a95b",
    messages=[{"role": "user", "content": "Hello"}],
)
Wire Qwen3.8 2.4T A95B into your product

1M free tokens to start, no card required. It’s OpenAI-compatible, so you only change the base URL.

Start free