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Qwen: Qwen3.8 2.4T A95B

Source description (English)

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, with 95 billion active parameters out of 2.4 trillion total. It is...

View source on OpenRouter Hugging Face
Overview

Model specifications

Context
1,048,576 tokens
Maximum output
131,072 tokens
Architecture
text->text
Tokenizer
Qwen
Knowledge cutoff
Not provided
Moderated
No
OPENROUTER

Complete pricing

Synchronized OpenRouter rates. Token prices are shown per one million tokens.

Input
$2
per 1M tokens
Output
$6
per 1M tokens
Cache read
$0.25
per 1M tokens
API

Model configuration

Default parameters

temperature
1
top_p
0.95
top_k
20

Reasoning

Reasoning required
Yes
Default parameters
xhigh
Capabilities
xhigh, medium, low
API

Quick start

Set OPENROUTER_API_KEY locally. Python requires requests; JavaScript runs in Node.js. Keep the key on the server.

API documentation

curl --fail-with-body https://openrouter.ai/api/v1/chat/completions \
  -H "Authorization: Bearer $OPENROUTER_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{"model":"qwen/qwen3.8-2.4t-a95b","messages":[{"role":"user","content":"Hello!"}]}'
Capabilities

Input → Output

Input
text
Output
text
Reasoning

Yes · xhigh · medium · low

API

Supported API parameters

frequency_penaltyinclude_reasoninglogit_biaslogprobsmax_tokensmin_ppresence_penaltyreasoningreasoning_effortrepetition_penaltyresponse_formatseedstopstructured_outputstemperaturetool_choicetoolstop_ktop_logprobstop_p
Available providers

7 providers

Checked: September 9, 2026

Live providers on OpenRouter

Provider availability, latency, throughput and routing can change continuously. Open the source page for current operational data.

OpenRouter

Novita

Not provided
Context
1M
Maximum output
131K
Input
$2
Output
$6
Cache read
$0.25
Cache write
Not provided

Alibaba

Not provided
Context
1M
Maximum output
131K
Input
$2
Output
$6
Cache read
$0.25
Cache write
$2.5

SiliconFlow

fp8
Context
1.0M
Maximum output
131K
Input
$2
Output
$6
Cache read
$0.25
Cache write
Not provided

Modal

Not provided
Context
1M
Maximum output
262K
Input
$2
Output
$6
Cache read
$0.25
Cache write
Not provided

DeepInfra

fp4
Context
262K
Maximum output
131K
Input
$2
Output
$6
Cache read
$0.2
Cache write
Not provided

Together

Not provided
Context
1.0M
Maximum output
909K
Input
$2
Output
$6
Cache read
$0.25
Cache write
Not provided

Venice

Not provided
Context
262K
Maximum output
66K
Input
$2.5
Output
$7.5
Cache read
$0.3125
Cache write
Not provided
qwen

4 models

All models
qwen logoqwen

Qwen: Qwen3.8 Omni Flash

Qwen3.8 Omni Flash is an omni-modal reasoning model from Alibaba, the first Qwen model built around agentic capabilities with native audio-video understanding. It is suited for audio-video analysis and summarization,...

Context
1M
Input
text · image · audio · video
Output
text
Input: $0.15Output: $0.47per 1M tokens
View model details →
qwen logoqwen

Qwen: Qwen3.8 Max (0902)

Qwen3.8 Max 0902 is an updated snapshot of Qwen3.8 Max from Alibaba's Qwen team. It is a 2.4-trillion-parameter mixture-of-experts model that accepts text, image, and video input and returns text,...

Context
1M
Input
text · image · video
Output
text
Input: $2Output: $6per 1M tokens
View model details →
qwen logoqwen

Qwen: Qwen3.8 Flash

Qwen3.8 Flash is a multimodal reasoning model from Alibaba. It is suited for coding assistance, agentic workflows, visual understanding, document and codebase analysis, desktop interaction, chart analysis, and long-video analysis.

Context
1M
Input
text · image · video
Output
text
Input: $0.15Output: $0.47per 1M tokens
View model details →
qwen logoqwen

Qwen: Qwen3.8 27B

Qwen3.8 27B is an open-weight dense vision-language model from Qwen. It is suited for coding, professional workflows, research, multimodal interaction, and long-running agent tasks, with flexible thinking that can be...

Context
1M
Input
text · image · video
Output
text
Input: $0.42Output: $3per 1M tokens
View model details →