Ling-3.0-flash
InclusionAI · released Jul 23, 2026
*Ling-3.0-flash* is a *124B-parameter Mixture-of-Experts (MoE) model*, with approximately *5.1B parameters activated per token*. The model is designed with *token efficiency and production-scale agentic inference* as key priorities, enabling developers...
Specification
- Context window
- 262K
- Max output
- 33K
- Knowledge cutoff
- Not stated
- Parameters
- 127.5B
- Licence
- mit
- Serving providers
- 2
- Moderated
- No
- Uptime
- 100.0%
Intelligence
37.8
85th percentile
Coding
50.6
Coding Index
Agentic
—
Agentic Index
Output speed
211 t/s
Median across providers
Latency
293ms
Time to first token
Cost per task
$0.006
Estimated
Benchmarks
Where the score comes from
The Intelligence Index is a composite. These are the underlying evaluations this model was actually measured on.
Evaluation scores
Percentage correct · higher is better
- GPQA Diamond85.5%
- AA-LCR (long context)67.0%
- SciCode41.1%
- τ²-bench (Telecom)27.2%
- Humanity's Last Exam23.7%
An evaluation missing from this list was not run for this model — it is not a zero.
View as table
| Evaluation | Score |
|---|---|
| GPQA Diamond | 85.5% |
| AA-LCR (long context) | 67.0% |
| SciCode | 41.1% |
| τ²-bench (Telecom) | 27.2% |
| Humanity's Last Exam | 23.7% |
Against its peers
Intelligence Index · this model highlighted, nearest peers in grey
- MiMo-V2.5Xiaomi38.0
- Grok 4.20xAI38.0
- Grok 4.3xAI37.9
- Ling-3.0-flashInclusionAI37.8
- Qwen3.6 27BQwen37.7
- GPT-5.1OpenAI37.5
- Gemini 3.5 Flash LiteGoogle37.4
- Claude Sonnet 4.6Anthropic36.8
Peers are the models sitting closest on the Intelligence Index — the set you would realistically choose between.
View as table
| Model | Intelligence |
|---|---|
| MiMo-V2.5 | 38.0 |
| Grok 4.20 | 38.0 |
| Grok 4.3 | 37.9 |
| Ling-3.0-flash | 37.8 |
| Qwen3.6 27B | 37.7 |
| GPT-5.1 | 37.5 |
| Gemini 3.5 Flash Lite | 37.4 |
| Claude Sonnet 4.6 | 36.8 |
Percentile among all indexed models
Pricing
What it costs to run
List prices per million tokens, plus what one representative task works out to.
List price
- Input / 1M tokens
- $0.021
- Output / 1M tokens
- $0.063
- Cached input / 1M
- $0.004
- Blended 3:1
- $0.032
One task, estimated
$0.006
- Input tokens
- 50,000
- Output tokens
- 80,000
- Profile
- Reasoning
Estimated from list pricing: 50K input tokens plus 80K output tokens for reasoning models (25K for non-reasoning).