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InclusionAI

Ling 3.0 Flash

  • Released
  • Open weights
  • MIT
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Intelligence Index

Reasoning setting

20.1
Measured · Artificial Analysis v4.3.2
API price from
$0.06 in / $0.18 out / 1M tokOpenRouter · DeepInfra · BF16
Context window
262.14K tok

Performance profile

ReasoningArchived source
85.5%
GPQA Diamond
CodingArchived source
42.0%
SciCode

Capabilities

Context window

Modalities

Measured setting

Integration

Reasoning trade-offs

Source (opens in a new tab)
Intelligence Index v4.3.2
Reasoning
Intelligence Index
20.1
Evaluation time
2.0m

Pricing & access

API route
OpenRouter · DeepInfra · BF16API
Tier & contextStandard

USD per 1M tokens

Input
$0.06
Output
$0.18
Cached input
$0.012

Run locally

GGUF
Context
Estimated memory

~79.8 GiB

RAM + VRAM

Estimate assumptions

One text chat at the selected context, with a 16-bit cache and app allowance. Operating system and image processing are extra; optimized caches can use less.

96 GiB RAMwithout GPU offload

Memory budgetOne text chat
Weights
72.5 GiB
Context + state
0.1 GiB16-bit cache
App allowance
7.2 GiB
Download
77.8 GB2 files · keep together
Disk space
~91 GB
Available software
Ollama (opens in a new tab)LM Studio (opens in a new tab)Jan (opens in a new tab)KoboldCpp (opens in a new tab)llama.cpp (opens in a new tab)
Get GGUF (opens in a new tab)
Set up in Ollama · Q4_K_M · 8K context

Save the following as Modelfile. The context matches the estimate above.

FROM hf.co/bartowski/Ling-3.0-flash-GGUF:Q4_K_M
PARAMETER num_ctx 8192

Then run these commands in your terminal:

ollama create llmcurrent-local -f Modelfile
ollama run llmcurrent-local

Ollama import instructions (opens in a new tab) · For LM Studio or Jan, open the app’s model search, enter bartowski/Ling-3.0-flash-GGUF, choose Q4_K_M, and set context to 8,192 tokens in the app’s model settings. Software links above open each app’s setup guide.

vLLM setup (opens in a new tab)

Benchmarks

Full leaderboardSource (opens in a new tab)

Humanity’s Last Exam

Frontier reasoning

Ling 3.0 Flash · ReasoningArchived

  1. 1Claude Opus 5.5Max61.4%
  2. 2Claude Fable 5.1Max59.1%
  3. 3Gemini 4 ArgonHigh57.1%
  4. 4Claude Sonnet 5.5Max55.0%
  5. 5GPT-6 AstraMax54.7%
  6. 6Muse Wonder FullMax53.6%
  7. 7GPT-6.1 SolMax52.9%
  8. 8Muse WonderMax50.1%
  9. 9MiMo-V2.6-ProReasoning49.4%
  10. 10Muse Spark 1.3Max48.7%

Peers use their best measured result on this benchmark.