Ling 3.0 Tiny Intelligence, Performance & Price Analysis
Model summary
Ling 3.0 Tiny is amongst the leading models in intelligence and well priced when comparing to other open weight models of similar size. It's also notably fast, however very verbose. The model supports text input, outputs text, and has a 262k tokens context window.
Ling 3.0 Tiny scores 25 on the Artificial Analysis Intelligence Index, placing it well above average among comparable models (median: 9). When evaluating the Intelligence Index, it generated 210M tokens, which is very verbose in comparison to the median of 48M.
Pricing for Ling 3.0 Tiny is $0.00 per 1M input tokens (competitively priced, median: $0.05) and $0.00 per 1M output tokens (competitively priced, median: $0.17). In total, it cost $0.00 to evaluate Ling 3.0 Tiny on the Intelligence Index.
At 154 tokens per second, Ling 3.0 Tiny is notably fast (103).
| Reasoning | Yes This page shows the reasoning version of this model. A non-reasoning variant may also exist. |
|---|---|
| Input modality | Supports: text |
| Output modality | Supports: text |
| Context window | 262k ~393 A4 pages of size 12 Arial font |
| Total parameters | 7.9B |
| Active parameters | 1.3B Number of parameters active per token during inference |
| License | Mit |
| Model weights | Hugging Face |
Metrics are compared against models of the same class:
- Non-reasoning models → compared only with other non-reasoning models
- Reasoning models → compared across both reasoning and non-reasoning
- Open weights models → compared only with other open weights models of the same size class:
- Tiny: ≤4B parameters
- Small: 4B–40B parameters
- Medium: 40B–150B parameters
- Large: >150B parameters
- Proprietary models → compared across proprietary and open weights models of the same price range, using a blended 3:1 input/output price ratio:
- <$0.15 per 1M tokens
- $0.15–$1 per 1M tokens
- >$1 per 1M tokens
Highlights
Intelligence
Artificial Analysis Intelligence Index
Artificial Analysis Intelligence Index by Open Weights / Proprietary
Intelligence Evaluations
Agentic real-world work tasks, (Elo-500)/2000
Agentic tool use
Agentic coding & terminal use
Coding
Reasoning & knowledge
Scientific reasoning
Physics reasoning
Knowledge
1 - hallucination rate
Long context reasoning
Agentic knowledge work, Elo
Agentic SaaS workflows
Legal agentic work, criterion pass rate
Agentic business operations
Quantitative analysis on spreadsheets & documents
Instruction following
Long-horizon agentic tasks
Kubernetes incident root-cause analysis
Visual reasoning
AA-Omniscience
AA-Omniscience Index
Openness Index
Artificial Analysis Openness Index: Score
Intelligence Index Comparisons
Intelligence Index vs. Cost per Intelligence Index Task
Token Use
Output Tokens per Intelligence Index Task
Cost
Cost per Intelligence Index Task
Cost to Run Artificial Analysis Intelligence Index
Pricing: Cache Hit, Input, and Output
Context Window
Context Window
Speed
Measured by Output Speed (tokens per second)
Output Speed
Time per Intelligence Index Task
Latency
Measured by Time (seconds) to First Token
Latency: Time To First Answer Token
End-to-End Response Time
Seconds to output 500 tokens, calculated based on time to first token, 'thinking' time for reasoning models, and output speed
End-to-End Response Time
Model Size (Open Weights Models Only)
Model Size: Total and Active Parameters
Frequently Asked Questions
Common questions about Ling 3.0 Tiny
Ling 3.0 Tiny was released on August 6, 2026.
Ling 3.0 Tiny was created by InclusionAI.
Ling 3.0 Tiny scores 25 on the Artificial Analysis Intelligence Index, placing it well above average among other open weight models of similar size (median: 9).
Ling 3.0 Tiny generates output at 154.0 tokens per second (based on the median across providers serving the model), which is well above average compared to other open weight models of similar size (median: 103.2 t/s).
Ling 3.0 Tiny has a time to first token (TTFT) of 2.61s (based on the median across providers serving the model), which is at the higher end compared to other open weight models of similar size (median: 2.02s).
When evaluated on the Intelligence Index, Ling 3.0 Tiny generated 210M output tokens, which is at the higher end compared to other open weight models of similar size (median: 48M).
Yes, Ling 3.0 Tiny is a reasoning model. It uses extended thinking or chain-of-thought reasoning to work through complex problems before providing an answer.
Ling 3.0 Tiny supports text input.
Ling 3.0 Tiny supports text output.
No, Ling 3.0 Tiny does not support image input. It can only process text.
No, Ling 3.0 Tiny is not multimodal. It only supports text input.
Ling 3.0 Tiny has a context window of 260k tokens. This determines how much text and conversation history the model can process in a single request.
Yes, Ling 3.0 Tiny is open weights. The model weights are publicly available and can be downloaded for self-hosting.
Ling 3.0 Tiny has 7.9 billion parameters (1.3 billion active).
Ling 3.0 Tiny is a Mixture of Experts (MoE) model with 7.9 billion total parameters, but only 1.3 billion active parameters are used during inference.
Ling 3.0 Tiny is released under the Mit license. This license allows commercial use. View license
Ling 3.0 Tiny achieves a score of 25 on the Artificial Analysis Intelligence Index. This composite benchmark evaluates models across reasoning, knowledge, mathematics, and coding.
Yes, Ling 3.0 Tiny is available via API through 2 providers. Compare API providers
Ling 3.0 Tiny is available through 2 API providers. Compare providers