Ling 3.0 Tiny
Intelligence benchmarks
Artificial Analysis indexes - compared with the best open and proprietary models
Intelligence
24.5
AA Index
Agentic
16.0
AA Index
Intelligence Index - Ling 3.0 Tiny vs. the field
Best open-weight models (you can run locally) and leading proprietary models for context.
Agentic Index comparison
Benchmark data from Artificial Analysis · updated 2026-08-15.
Standard benchmarks
Performance across standard evaluations
| Benchmark | Score |
|---|---|
| GPQA | 73.4 |
Will it run on your hardware?
Pick your GPU memory - see which quantizations fit, and the cheapest card for the rest
Need an exact figure for your context length? Use the VRAM calculator.
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Deep dive
Notes, sources, and the full write-up
Ling 3.0 Tiny is a 7.9B-parameter mit model from InclusionAI. It scores 24.5 on the Artificial Analysis Intelligence Index. At Q4_K_M it needs roughly 5 GB of VRAM, placing it in the 8–12 GB GPU hardware tier.
Benchmarks
Artificial Analysis Intelligence Index - Ling 3.0 Tiny vs. leading closed models:
| Model | Intelligence | Coding | GPQA |
|---|---|---|---|
| Ling 3.0 Tiny | 24.5 | - | 73.4 |
| Claude Opus 5 (max) | 63.1 | - | 93.2 |
| Claude Fable 5 (with fallback) | 62.1 | - | 92.6 |
| GPT-5.6 Sol (max) | 60.9 | - | 94.1 |
| Grok 4.6 (high) | 60.9 | - | 94.9 |
| Qwen3.8 Max | 58.1 | - | 92.7 |
Source: Artificial Analysis (2026-08-13).
Popularity
Ling 3.0 Tiny has 0 downloads in the last month on HuggingFace and 190 likes.
Frequently asked
Quick answers to common questions
How much VRAM does Ling 3.0 Tiny need?
Ling 3.0 Tiny with 7.9B parameters needs approximately 5 GB at Q4_K_M quantization. Use our VRAM calculator for an exact estimate.
Is Ling 3.0 Tiny better than other inclusionAI models?
Ling 3.0 Tiny has 7.9B parameters with 131,072 context - a strong choice for general use.
What license is Ling 3.0 Tiny under?
Ling 3.0 Tiny is released under the mit license, making it suitable for most commercial and personal projects.
What hardware runs Ling 3.0 Tiny well?
With 7.9B parameters, Ling 3.0 Tiny requires adequate VRAM. High-end GPUs like the RTX 4090 (24GB), RTX 5090 (32GB), or Mac Studio with unified memory are good options. Check our hardware directory for specific recommendations.
What is the best quantization for Ling 3.0 Tiny?
Q4_K_M is the recommended sweet spot - ~98% of FP16 quality at ~27% of the size. Q5_K_M (~6 GB) is an option if you have spare VRAM. Use our VRAM calculator to compare.
How long can Ling 3.0 Tiny's context window handle?
Ling 3.0 Tiny supports a 131,072-token context window - enough for very long documents, codebases, or multi-turn conversations. Real-world usable context may vary by implementation.
What models compete with Ling 3.0 Tiny?
Ling 3.0 Tiny competes with other models in its class. Browse our model directory for comparisons, benchmarks, and community reviews to find the best fit.
Nearby options
Similar models and compatible hardware by spec
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