Ling 3.0 Flash
inclusionai/ling-3.0-flashLing-3.0-flash prioritizes token efficiency and agentic inference at production scale within limited token, latency and serving-cost budgets.
IN
Ling 3.1 Flash
75% offLing-3.1-flash is an upgraded native hybrid reasoning model (560B total, 25B active) with a 1M-token context window, built for complex real-world tasks.
Context
262K
Max output
131K
Input /1M
$0.07$0.30
Output /1M
$0.22$0.90
Blended /1M
$0.11$0.45
AcceptsTextProducesTextTokenizer Other
Launch offer · 75% off on every provider
Applied automatically; prices return to list when each offer ends.
Price schedule by provider
DiscountedList price
DeepInfra$0.30 / $0.90
-75% · ongoing
-75% · ongoingToday · Nov 4Nov 18
Price after offer (in/out)Providers
FastRouter routes your requests to this provider. You can also bring your own key.
ProviderInput /1MOutput /1MContextMax outputLatencyThroughputOfferFeaturesDetails
DeepInfrafp4
deepinfraInput /1M$0.30$0.07
Output /1M$0.90$0.22
Context262K
Max output131K
Latency—
Throughput—
Offer
-75%Ongoing
Supports tool callingSupports structured (JSON) outputSupports reasoning
Offers without an end date apply until further notice.
Supported parameters
Request parameters you can send with this model.
Core (Sampling & basic generation)
- max_tokens
- Maximum tokens to generate.
- min_p
- Minimum probability threshold for sampling.
- seed
- Seed for deterministic sampling.
- stop
- Sequences where generation stops.
- temperature
- Controls randomness of output.
- top_k
- Limits sampling to top K tokens.
- top_p
- Nucleus sampling threshold.
Penalties (Token Penalties)
- frequency_penalty
- Penalizes frequent tokens.
- presence_penalty
- Penalizes tokens already present.
- repetition_penalty
- Penalizes repeated tokens.
Reasoning (Reasoning Controls)
- include_reasoning
- Include reasoning trace in the response.
- reasoning
- Provider-specific reasoning configuration.
Tool Use (Function Calls & Tools)
- tool_choice
- How the model should use tools.
- tools
- Tool/function definitions available to the model.
Output & Format (Response Formatting)
- logprobs
- Return log probabilities of output tokens.
Performance
Median throughput and time to first token per provider over the last week.
Throughput
Latency
Make your first API call
OpenAI-compatible. Point your SDK at FastRouter, or call the API directly.
Replace
<FASTROUTER_API_KEY> with your key · Get your key →Installfrom openai import OpenAI
client = OpenAI(
base_url="https://api.fastrouter.ai/api/v1", # FastRouter base URL
api_key= "<FASTROUTER_API_KEY>", # Replace with your FastRouter API key
)
completion = client.chat.completions.create(
model="inclusionai/ling-3.1-flash", # Replace with your model ID
messages=[
{ "role": "user", "content": "What is the meaning of life?" }
]
)
print(completion.choices[0].message.content)
Frequently asked questions
More models from inclusionAI
Model scores sourced from ArtificialAnalysis