inclusionai · Open weights
Ling 3.0 Flash VL
Ling 3.0 Flash VL is inclusionAI's native multimodal Mixture-of-Experts model with 124B total parameters and 5.5B active parameters per token. It combines image and video understanding with reasoning and tool use for document analysis, charts, visual verification, and interface-based agent tasks. Thinking is enabled by default and can be turned off in settings.
- Reasoning
- Tools
- Vision
- Video input
- Input
- Text, Images, Video
- Output
- Text
- Reasoning effort
- none · low · medium · high
- Discovery tier
- Open weights
Pricing
USD per 1M tokens- Input
- $0.06
- Output
- $0.18
- Cache read
- $0.012
Reference prices as published by the model provider. API example
Specifications
- Context window
- 262.1K
- Max output
- 32.8K
- Average output (7 days)
- 843 tokens
- Longer than 66% of 465 models
Side by side
Ling 3.0 Flash VL compared
Specifications, prices, speed and benchmark scores next to each other. Benchmarks below show every compared model too.
| Ling 3.0 Flash VLinclusionaiThis model | InklingthinkingmachinesRemove | |
|---|---|---|
| Provider | inclusionai | thinkingmachines |
| Discovery tier | Open weights | Open weights |
| Added | Sep 9, 2026 | Jul 15, 2026 |
| Limits | ||
| Context window | 262.14K | 1.05MBest |
| Max output | 32.77K | 32.77K |
| Average output | 843 tokens | 596 tokens |
| Pricing, USD per 1M tokens | ||
| Input | $0.06Best | $1.00 |
| Output | $0.18Best | $4.05 |
| Cache read | $0.012Best | $0.17 |
| Performance | ||
| Request success (24h) | 99.5% | 100.0%Best |
| Benchmark indexes | ||
| Intelligence Index | 24.6 | 25.0Best |
| Coding Index | 57.0Best | 52.1 |
| Capabilities | ||
| Reasoning | Yes | No |
| Tools | Yes | Yes |
| Vision | Yes | Yes |
| Structured output | No | Yes |
| Audio input | No | Yes |
| Video input | Yes | No |
| Reasoning effort | none, low, medium, high | — |
Public evaluations
Benchmarks
Independent evaluation results, with how each score ranks among the models in the Noumen catalog.
- Ling 3.0 Flash VL
- Inkling
Intelligence Index
- Ling 3.0 Flash VL24.6
- Inkling25.0
Ling 3.0 Flash VL: Better than 59% of 326 scored models
Indexes
Coding Index
Composite of the coding evaluations
- Ling 3.0 Flash VL: 57.0Top
- Inkling: 52.1
Agentic work
AutomationBench-AA
Workflow automation, penalized for guardrail violations
- Ling 3.0 Flash VL: 15.7%Top
- Inkling: 5.0%
AutomationBench-AA tasks completed
Workflows finished end to end without a guardrail violation
- Ling 3.0 Flash VL: 1.1%Top
- Inkling: 0.3%
Harvey LAB-AAv1.1
Legal tasks passed in full, with no material hallucination
- Ling 3.0 Flash VL: —
- Inkling: 0.0%
AA-Briefcasev1.1
Agentic knowledge work, rated head to head
- Ling 3.0 Flash VL: 984 EloTop
- Inkling: 832 Elo
GDPval-AAv2.1
Economically valuable occupational tasks, rated head to head
- Ling 3.0 Flash VL: 1,161 EloTop
- Inkling: 1,072 Elo
Document reasoning
GDP.pdf
Professional reasoning over PDF documents, all-pass rate
- Ling 3.0 Flash VL: 8.4%
- Inkling: 12.8%Top
AA-LCRv1.1
Reasoning across long documents
- Ling 3.0 Flash VL: 78.3%Top
- Inkling: 77.3%
MLCR-AA
Long-context reasoning over medical records
- Ling 3.0 Flash VL: 5.0%
- Inkling: 6.1%Top
Reasoning and knowledge
Humanity’s Last Exam
Expert-level questions across academic fields
- Ling 3.0 Flash VL: 22.0%
- Inkling: 31.9%Top
GPQA Diamond
Graduate-level science questions
- Ling 3.0 Flash VL: 86.2%
- Inkling: 87.2%Top
Coding
Terminal-Benchv4.0
Practical software engineering in a terminal
- Ling 3.0 Flash VL: 0.0%
- Inkling: 1.0%Top
SciCode
Scientific computing in Python
- Ling 3.0 Flash VL: 44.2%
- Inkling: 47.0%Top
Legacy evaluations
AA-LCR (unversioned)
Long-context reasoning, earlier grading
- Ling 3.0 Flash VL: 78.3%Top
- Inkling: 77.3%
Scores from Artificial Analysis, updated Oct 26, 2026. Artificial Analysis
- Ling 3.0 Flash VL
- Inkling
| Leaderboard | Ling 3.0 Flash VL | Inkling |
|---|---|---|
| EQ-Bench 4 | Not in top 20 | #15 · 1216 |
Ranks among Noumen catalog models on EQ-Bench leaderboards. Only top-20 placements are listed.EQ-Bench
Live routing data
Performance and reliability
Recent averages across requests routed for this model. Your own speed depends on prompt length, reasoning effort and load.
- Prompt cache hits
- 0.0%
- About $0.06 per 1M input tokens with caching
- Request success (24h)
- 99.5%
- Reliable
Cache hits are the share of input tokens recently served from a prompt cache across all requests. They are not a forecast of your own hit rate.
- Healthy (98% or more)
- Degraded (90–98%)
- Down (under 90%)
- No requests
Developers
Use it through the API
Noumen’s API is OpenAI-compatible: any Chat Completions client works with a base URL and a key.
curl https://www.noumen.xyz/api/v1/chat/completions \
-H "Authorization: Bearer $NOUMEN_API_KEY" \
-H "Content-Type: application/json" \
-d '{
"model": "inclusionai/ling-3.0-flash-vl",
"reasoning_effort": "medium",
"messages": [{ "role": "user", "content": "Explain this stack trace." }]
}'import os
from openai import OpenAI
client = OpenAI(base_url="https://www.noumen.xyz/api/v1", api_key=os.environ["NOUMEN_API_KEY"])
reply = client.chat.completions.create(
model="inclusionai/ling-3.0-flash-vl",
messages=[{"role": "user", "content": "Explain this stack trace."}],
)
print(reply.choices[0].message.content)inclusionai
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