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  4. Ling 3.0 Tiny
InclusionAI
Released August 6, 2026

Ling 3.0 Tiny

Ling 3.0 Tiny by InclusionAI is a 7.9B MoE model with 1.3B active parameters for responsive agents, multi-turn conversations, and switchable thinking modes.

Visit InclusionAI
Inputs
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Outputs
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Model Overview

Capabilities, design details, and architectural traits

Ling 3.0 Tiny - Low-Active-Compute MoE for Responsive Agents

Ling 3.0 Tiny is a mixture-of-experts model from InclusionAI that activates only a small fraction of its parameters per token. This unusually low active-compute ratio is the model's defining design choice, enabling it to serve agent and multi-turn conversation workloads with minimal per-token cost.

The model supports switchable Thinking and Instant modes, letting callers choose between deeper reasoning and fast responses within the same deployment. It also includes native function calling and prompt caching for tool-using, long-context workflows.

TraitDetail
ArchitectureMoE with low active-compute ratio
Switchable modesThinking mode and Instant mode, selectable per request
Agent design focusBuilt for responsive agents, instruction following, and multi-turn conversations
Tool supportNative function calling and prompt caching
Context window256K tokens with up to 32K max output
I/O modalityText input, text output only

Thinking vs. Instant Modes

The switchable Thinking and Instant modes distinguish Ling 3.0 Tiny from single-mode models in its class. Thinking mode engages deeper reasoning for complex prompts, while Instant mode prioritizes low-latency responses for conversational turns where speed matters more than extended deliberation.

Benchmark Performance

Independent evaluations · Artificial Analysis

24.5%
Intelligence
26.5%
Coding Index
16.0%
Agentic Index

Accuracy & Capability Details

GPQA - Graduate Science73.4%
Humanity's Last Exam9.3%
SciCode - Scientific Coding24.2%
Long Context Reasoning58.7%
Specs
Context window
262Ktokens

Prices in USD.

Compare Models Side-by-Side

Evaluate specifications, pricing, and independent benchmark indices

Model Details
General Info
ProviderInclusionAIAnthropicAnthropic
Release DateAugust 6, 2026July 24, 2026June 9, 2026
Knowledge Cutoff-May 2026-
Context & Limits
Context Window262K
1M
Best Context Window
1M
Best Context Window
Pricing (per 1M tokens)
Input Pricing
Free
Best Input Pricing
$5$10
Output Pricing
Free
Best Output Pricing
$25$50
Modalities
Inputs
text
textimage
textimagefile
Outputs
text
text
text
Benchmarks (0-100)
Intelligence Index24.5
63.1
Best Intelligence Index
62.1
Coding Index26.5
78.0
Best Coding Index
76.5
Agentic Index16.0
59.2
Best Agentic Index
56.6
Ling 3.0 Tiny
Claude Opus 5
Claude Fable 5

GPQA Benchmark

Graduate-level reasoning and expert Q&A evaluation.

73%
Ling 3.0 Tiny
GPQA Benchmark
Score: 73%
Ling 3.0 Tiny
93%
Claude Opus 5
GPQA Benchmark
Score: 93%
Claude Opus 5
93%
Claude Fable 5
GPQA Benchmark
Score: 93%
Claude Fable 5

Humanity's Last Exam

Extremely difficult logical reasoning and knowledge.

9%
Ling 3.0 Tiny
Humanity's Last Exam
Score: 9%
Ling 3.0 Tiny
55%
Claude Opus 5
Humanity's Last Exam
Score: 55%
Claude Opus 5
56%
Claude Fable 5
Humanity's Last Exam
Score: 56%
Claude Fable 5

Long Context Reasoning

Logical reasoning over long context windows.

59%
Ling 3.0 Tiny
Long Context Reasoning
Score: 59%
Ling 3.0 Tiny
76%
Claude Opus 5
Long Context Reasoning
Score: 76%
Claude Opus 5
77%
Claude Fable 5
Long Context Reasoning
Score: 77%
Claude Fable 5

Independent evaluation data provided by Artificial Analysis. To view the latest benchmarks and full details, visit their official site.

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