Alibaba · model passport
Qwen: Qwen3.8 2.4T A95B
qwen3-8-2-4t-a95b- Open weights
- 2.45T params
- 1,048,576 context
- Released 2026-08-08(HF repo created)
How to run it
Run it yourself
RepositoryQwen/Qwen3.8-2.4T-A95B
Parameters2.45T
ArchitectureQwen3_5MoeForCausalLM
Transformers
from transformers import AutoModelForCausalLM, AutoTokenizer
model_id = "Qwen/Qwen3.8-2.4T-A95B"
tokenizer = AutoTokenizer.from_pretrained(model_id)
model = AutoModelForCausalLM.from_pretrained(model_id)Ollama
We don't sync Ollama tags, so we won't print a command we can't verify — a wrong one would pull the wrong model. Search the Ollama library →
Unsloth fine-tuning recipes are model-specific and we don't derive them here. Unsloth docs →
Use it hosted
API model ID
qwen/qwen3.8-2.4t-a95bContext length1,048,576 tokens
Max output131,072 tokens
Input price$2 per 1M tokens
Cached input price$0.25 per 1M tokens
Output price$6 per 1M tokens
API parameters this endpoint supports
Frequency penaltyInclude reasoningLogit biasLogprobsMax tokensMin-pPresence penaltyReasoningReasoning effortRepetition penaltyResponse formatSeedStop sequencesStructured outputsTemperatureTool choiceTool callingTop-kTop logprobsTop-p
Example request
curl 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"}]}'Identifiers, limits and prices are synced from the upstream source shown above. Any field we haven't synced is left out entirely rather than guessed.
No benchmark we track has published a result for this model yet, so there is no score card — only the run guide above. It will appear here once any board we ingest scores it.