Inclusionai · model passport
inclusionAI: Ling 3.0 Flash
ling-3-0-flash- Open weights
- 127.5B params
- 262,144 context
How to run it
Run it yourself
RepositoryinclusionAI/Ling-3.0-flash
Parameters127.5B
ArchitectureBailingMoeV3ForCausalLM
Transformers
from transformers import AutoModelForCausalLM, AutoTokenizer
model_id = "inclusionAI/Ling-3.0-flash"
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
inclusionai/ling-3.0-flashContext length262,144 tokens
Max output32,768 tokens
Input price$0.02 per 1M tokens
Cached input price$0.00 per 1M tokens
Output price$0.06 per 1M tokens
API parameters this endpoint supports
Frequency penaltyInclude reasoningLogit biasLogprobsMax tokensMin-pPresence penaltyReasoningRepetition penaltyResponse formatSeedStop sequencesTemperatureTool 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":"inclusionai/ling-3.0-flash","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.