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Models

Ling-3.0-flash-Fin

By inclusionAI. 127.5 billion parameters, a context window of 262,144 tokens and the licence mit.

Facts

Released
2026-09-03 the day the repository was first published on Hugging Face Hugging Face, read
Licence
mit the licence the model card declares Hugging Face, read
Open weights
Yes the weights are published in this Hugging Face repository Hugging Face, read
Parameters
127.5 billion counted from the safetensors weight files Hugging Face, read
Active parameters
8.6 billion estimate estimated from the expert counts and sizes in the configuration model configuration, read
Knowledge cutoff
Unknown
Context window
  • 262,144 tokens the maximum position embeddings in the model configuration model configuration, read
Longest output
Unknown
Tool calling
Unknown
Structured output
Unknown
Reasoning controls
Unknown
Inputs and outputs
text in, text out Hugging Face, read
Good for
No source names a use.

Prices

Prices in US dollars per million tokens, as each source lists them
ProviderInputOutputContextAs ofSource
Vercel AI Gateway direct0 USD0 USD256,000models.dev, read
Kilo Gateway direct0.060 USD0.180 USD262,144models.dev, read
OpenRouter direct0.060 USD0.180 USD262,144models.dev, read

Run it on your own hardware

Weights are the sizes of the files a source lists, or an estimate from the parameter count where none does. Memory is an estimate: weights plus KV cache plus 512 MiB and 5 percent of the weights for runtime buffers. Check it against your hardware.

QuantizationWeightsMemory at 8,192 tokensMemory at 32,768 tokens
IQ1_S25.7 GiB27.8 GiB28.9 GiB
IQ1_M28.5 GiB30.8 GiB31.9 GiB
IQ2_XXS32.8 GiB35.3 GiB36.4 GiB
IQ2_XS36.4 GiB39.0 GiB40.2 GiB
IQ2_S37.0 GiB39.7 GiB40.8 GiB
IQ2_M40.6 GiB43.5 GiB44.7 GiB
Q2_K42.7 GiB45.8 GiB46.9 GiB
Q2_K_L43.1 GiB46.1 GiB47.2 GiB
IQ3_XXS50.4 GiB53.8 GiB54.9 GiB
Q3_K_S52.4 GiB55.9 GiB57.0 GiB
IQ3_XS54.9 GiB58.5 GiB59.6 GiB
Q3_K_M54.9 GiB58.5 GiB59.6 GiB
Q3_K_L57.2 GiB60.9 GiB62.0 GiB
IQ3_M57.3 GiB61.0 GiB62.1 GiB
Q3_K_XL57.5 GiB61.3 GiB62.4 GiB
IQ4_XS64.0 GiB68.1 GiB69.2 GiB
IQ4_NL67.6 GiB71.8 GiB72.9 GiB
Q4_067.8 GiB72.1 GiB73.2 GiB
Q4_K_S69.9 GiB74.3 GiB75.4 GiB
Q4_K_M72.5 GiB77.0 GiB78.1 GiB
Q4_K_L72.7 GiB77.2 GiB78.4 GiB
Q4_174.7 GiB79.3 GiB80.4 GiB
Q5_K_S81.9 GiB86.8 GiB87.9 GiB
Q5_K_M84.4 GiB89.5 GiB90.6 GiB
Q5_K_L84.7 GiB89.8 GiB90.9 GiB
Q6_K102 GiB108 GiB109 GiB
Q8_0126 GiB134 GiB135 GiB
BF16238 GiB250 GiB251 GiB

Start it with a local runtime

  • Ollama
    ollama run hf.co/bartowski/Ling-3.0-flash-Fin-GGUF:Q4_0
  • LM Studio
    lms get bartowski/Ling-3.0-flash-Fin-GGUF
    lms server start
  • llama.cpp server
    llama-server -hf bartowski/Ling-3.0-flash-Fin-GGUF:Q4_0 --jinja
  • vLLM
    vllm serve inclusionAI/Ling-3.0-flash-Fin
  • SGLang
    sglang serve --model-path inclusionAI/Ling-3.0-flash-Fin --port 30000

Use it from your harness

Set up for Kilo Gateway with the model inclusionai/ling-3.0-flash-fin. Each endpoint page has the same setup for its own address.

OpenCode

Put this in opencode.json in your project folder:

{
  "$schema": "https://opencode.ai/config.json",
  "provider": {
    "kilo": {
      "npm": "@ai-sdk/openai-compatible",
      "name": "Kilo Gateway",
      "options": {
        "baseURL": "https://api.kilo.ai/api/gateway",
        "apiKey": "{env:KILO_API_KEY}"
      },
      "models": {
        "inclusionai/ling-3.0-flash-fin": {
          "name": "Ling-3.0-flash-Fin"
        }
      }
    }
  }
}
  • OpenCode reads any OpenAI-compatible address through the @ai-sdk/openai-compatible package, and an address that speaks the Responses API through @ai-sdk/openai.

From OpenCode documentation, read .

Pi

Put this in ~/.pi/agent/models.json:

{
  "providers": {
    "kilo": {
      "baseUrl": "https://api.kilo.ai/api/gateway",
      "api": "openai-completions",
      "apiKey": "$KILO_API_KEY",
      "models": [
        {
          "id": "inclusionai/ling-3.0-flash-fin"
        }
      ]
    }
  }
}
  • The apiKey field can name an environment variable as $NAME.

From Pi documentation, read .

Codex

Codex speaks only the Responses API, and Kilo Gateway documents no Responses address. A gateway that offers one can sit in between.

  • Codex speaks the Responses API only: responses is the one supported wire API of a custom provider. Ollama and LM Studio are built in and start with --oss.

From Codex documentation, read .

Claude Code

Claude Code sends Anthropic Messages requests, and Kilo Gateway documents no such address. A gateway that translates to that API can sit in between.

  • Claude Code sends Anthropic Messages requests to ANTHROPIC_BASE_URL. Anthropic says it does not support routing Claude Code to models other than Claude through any gateway, so some features may not work with another model.

From Claude Code documentation, read .

Other ways to reach it

  • OpenRouter, model inclusionai/ling-3.0-flash-fin
  • Ollama, model hf.co/bartowski/Ling-3.0-flash-Fin-GGUF:Q4_0

Published results

These are results other people published. Baltor did not run them and does not rank models by them.