Total runs:
1.1M
Run Growth:
885.6K
Growth Rate:
78.28%
Sponsored by
APIMart
LiquidAI / LFM2-2.6B-Transcript
Model's Last Updated: March 31 2026
text-generation
Introduction of LFM2-2.6B-Transcript
Model Details of LFM2-2.6B-Transcript
LFM2-2.6B-Transcript
Based on LFM2-2.6B , LFM2-2.6B-Transcript is designed to private, on-device meeting summarization . We partnered with AMD to deliver cloud-level summary quality while running entirely locally, ensuring your meeting data never leaves your device.
Highlights :
- Cloud-level summary quality, approaching much larger models
- Under 3GB of RAM usage for long meetings
- Fast summaries in seconds, not minutes
- Runs fully locally across CPU, GPU, and NPU
You can find more information about other task-specific models in this blog post .
📄 Model details
Capabilities : The model is trained for long-form transcript summarization (30-60 minute meetings), producing clear, structured outputs including key points, decisions, and action items with consistent tone and formatting.
Use cases :
- Internal team meetings
- Sales calls and customer conversations
- Board meetings and executive briefings
- Regulated or sensitive environments where data can't leave the device
- Offline or low-connectivity workflows
Generation parameters
: We strongly recommend using a lower temperature with a
temperature=0.3
.
Supported language : English
⚠️ The model is intended for single-turn conversations with a specific format, described in the following.
System prompt : We recommend using the following system prompt:
You are an expert meeting analyst. Analyze the transcript carefully and provide clear, accurate information based on the content.
Input format : We use a specific formatting for the input meeting transcripts to summarize as follows:
Title (example: Claims Processing training module)
Participants (example: Julie Franco (Training Facilitator), Amanda Newman (Subject Matter Expert))
----------
**Speaker 1**: <Their dialogue goes here. This can span multiple sentences> (example: **Julie Franco**: Good morning, everyone. Thanks for joining me today.)
**Speaker 2**: <Their dialogue goes here. This can span multiple sentences> (example: **Amanda Newman**: Good morning, Julie. Happy to be here.)
etc.
<user_prompt>
Output format : You can specify what the model outputs among the following summary types:
| Summary type | User prompt |
|---|---|
executive_summary
|
Provide a brief executive summary (2-3 sentences) of the key outcomes and decisions from this transcript. |
detailed_summary
|
Provide a detailed summary of the transcript, covering all major topics, discussions, and outcomes in paragraph form. |
action_items
|
List the specific action items that were assigned during this meeting. Include who is responsible for each item when mentioned. |
key_decisions
|
List the key decisions that were made during this meeting. Focus on concrete decisions and outcomes. |
participants
|
List the participants mentioned in this transcript. Include their roles or titles when available. |
topics_discussed
|
List the main topics and subjects that were discussed in this meeting. |
Examples : You can find examples of meeting inputs and outputs here:
| Title | Input meeting | Model output |
|---|---|---|
| Budget planning | Link | Link |
| Design review | Link | Link |
| Coffee chat / social hour | Link | Link |
| Procurement / vendor review | Link | Link |
| Task force meeting | Link | Link |
🚀 Quick Start
The easiest way to try LFM2-2.6B-Transcript is through our command-line tool in the Liquid AI Cookbook .
1. Install uv (if you don't have it already):
uv --version
# uv 0.9.18
2. Run with the sample transcript :
uv run https://raw.githubusercontent.com/Liquid4All/cookbook/refs/heads/main/examples/meeting-summarization/summarize.py
No API keys. No cloud services. No setup. Just pure local inference with real-time token streaming.
3. Use your own transcript :
uv run https://raw.githubusercontent.com/Liquid4All/cookbook/refs/heads/main/examples/meeting-summarization/summarize.py \
--transcript-file path/to/your/transcript.txt
The tool uses llama.cpp for optimized inference and automatically handles model downloading and compilation for your platform.
🏃 Inference
LFM2 is supported by many inference frameworks. See the Inference documentation for the full list.
| Name | Description | Docs | Notebook |
|---|---|---|---|
| Transformers | Simple inference with direct access to model internals. | Link |
|
| vLLM | High-throughput production deployments with GPU. | Link |
|
| llama.cpp | Cross-platform inference with CPU offloading. | Link |
|
| MLX | Apple's machine learning framework optimized for Apple Silicon. | Link | — |
| LM Studio | Desktop application for running LLMs locally. | Link | — |
📈 Performance
LFM2-2.6B-Transcript was benchmarked using the GAIA Eval-Judge framework on synthetic meeting transcripts across 8 meeting types.
| Model | Size | Short (1K tokens) | Long (10K tokens) |
|---|---|---|---|
| Claude Sonnet 4 | Cloud | 90% | 93% |
| Qwen3-30B-A3B-Instruct-2507 (Q4_0) | 30B | 88% | 92% |
| LFM2-2.6B-Transcript (Q4_K_M) | 2.6B | 86% | 77% |
| gpt-oss-20b (Q4_K_M) | 20B | 83% | 71% |
| Qwen3-8B (Q4_1) | 8B | 65% | 72% |
Accuracy ratings from GAIA LLM Judge. Evaluated on 24 synthetic 1K transcripts and 32 synthetic 10K transcripts. Claude Sonnet 4 used for content generation and judging.
📬 Contact
If you are interested in custom solutions with edge deployment, please contact our sales team .
Runs of LiquidAI LFM2-2.6B-Transcript on huggingface.co
516
Total runs
0
24-hour runs
0
3-day runs
-38
7-day runs
-17
30-day runs
More Information About LFM2-2.6B-Transcript huggingface.co Model
Url of LFM2-2.6B-Transcript
LFM2-2.6B-Transcript huggingface.co Url
Provider of LFM2-2.6B-Transcript huggingface.co
Other API from LiquidAI
Updated:August 25 2026
Total runs:
580.5K
Run Growth:
546.6K
Growth Rate:
97.12%
Total runs:
484.0K
Run Growth:
344.2K
Growth Rate:
72.42%
Total runs:
339.4K
Run Growth:
136.5K
Growth Rate:
39.78%
Total runs:
295.1K
Run Growth:
-271.3K
Growth Rate:
-91.93%
Total runs:
121.5K
Run Growth:
115.6K
Growth Rate:
99.19%
Total runs:
104.2K
Run Growth:
78.6K
Growth Rate:
75.40%
Total runs:
100.4K
Run Growth:
58.9K
Growth Rate:
58.70%
Total runs:
94.0K
Run Growth:
-38.8K
Growth Rate:
-41.26%
Total runs:
83.0K
Run Growth:
4.5K
Growth Rate:
5.38%
Total runs:
71.0K
Run Growth:
66.1K
Growth Rate:
99.09%
Total runs:
61.2K
Run Growth:
-10.4K
Growth Rate:
-17.02%
Total runs:
52.8K
Run Growth:
36.3K
Growth Rate:
68.79%
Total runs:
38.4K
Run Growth:
11.4K
Growth Rate:
29.65%
Total runs:
35.3K
Run Growth:
26.2K
Growth Rate:
70.18%
Total runs:
28.5K
Run Growth:
24.4K
Growth Rate:
85.46%
Total runs:
28.0K
Run Growth:
-5.1K
Growth Rate:
-18.24%
Total runs:
17.1K
Run Growth:
10.1K
Growth Rate:
59.44%
Total runs:
16.7K
Run Growth:
-1.1K
Growth Rate:
-6.75%
Total runs:
16.5K
Run Growth:
2.7K
Growth Rate:
16.31%
Total runs:
15.9K
Run Growth:
4.5K
Growth Rate:
28.32%
Total runs:
15.0K
Run Growth:
-24.0K
Growth Rate:
-159.48%
Total runs:
14.7K
Run Growth:
6.0K
Growth Rate:
40.65%
Total runs:
14.5K
Run Growth:
5.9K
Growth Rate:
40.36%
Total runs:
14.2K
Run Growth:
864
Growth Rate:
6.10%
Total runs:
12.1K
Run Growth:
8.4K
Growth Rate:
69.15%
Total runs:
12.1K
Run Growth:
2.0K
Growth Rate:
16.20%
Total runs:
11.1K
Run Growth:
-28.7K
Growth Rate:
-258.65%
Total runs:
10.5K
Run Growth:
-2.8K
Growth Rate:
-26.38%
Total runs:
10.3K
Run Growth:
2.6K
Growth Rate:
25.11%
Total runs:
8.6K
Run Growth:
3.0K
Growth Rate:
34.97%
Total runs:
6.4K
Run Growth:
4.3K
Growth Rate:
67.01%
Total runs:
6.4K
Run Growth:
3.2K
Growth Rate:
49.52%
Total runs:
6.1K
Run Growth:
-580
Growth Rate:
-9.47%
Total runs:
6.1K
Run Growth:
4.9K
Growth Rate:
81.12%
Total runs:
5.0K
Run Growth:
295
Growth Rate:
5.88%
Total runs:
4.2K
Run Growth:
4.1K
Growth Rate:
97.01%
Total runs:
4.1K
Run Growth:
2.7K
Growth Rate:
67.09%
Total runs:
4.1K
Run Growth:
2.3K
Growth Rate:
55.70%
Total runs:
4.0K
Run Growth:
-1.2K
Growth Rate:
-30.60%
Total runs:
4.0K
Run Growth:
-870
Growth Rate:
-22.03%
Total runs:
3.9K
Run Growth:
2.2K
Growth Rate:
56.04%
Total runs:
3.7K
Run Growth:
3.5K
Growth Rate:
94.89%
Total runs:
3.7K
Run Growth:
3.3K
Growth Rate:
89.89%
Total runs:
3.0K
Run Growth:
-879
Growth Rate:
-28.93%
Total runs:
3.0K
Run Growth:
1.3K
Growth Rate:
44.78%
Total runs:
2.9K
Run Growth:
232
Growth Rate:
7.89%
Total runs:
2.7K
Run Growth:
-11.8K
Growth Rate:
-445.17%
Total runs:
2.5K
Run Growth:
422
Growth Rate:
16.58%
Total runs:
2.4K
Run Growth:
1.9K
Growth Rate:
80.03%
Total runs:
2.4K
Run Growth:
101
Growth Rate:
4.27%
Total runs:
2.3K
Run Growth:
-1.1K
Growth Rate:
-45.94%
Total runs:
2.2K
Run Growth:
-494
Growth Rate:
-22.87%
Total runs:
2.1K
Run Growth:
879
Growth Rate:
41.54%
Total runs:
1.9K
Run Growth:
1.5K
Growth Rate:
75.59%
Total runs:
1.9K
Run Growth:
1.2K
Growth Rate:
63.35%
Total runs:
1.9K
Run Growth:
-591
Growth Rate:
-31.66%
Total runs:
1.8K
Run Growth:
1
Growth Rate:
0.06%
Total runs:
1.8K
Run Growth:
96
Growth Rate:
5.30%
Total runs:
1.8K
Run Growth:
-2.2K
Growth Rate:
-123.61%
Total runs:
1.7K
Run Growth:
-478
Growth Rate:
-28.49%
Total runs:
1.5K
Run Growth:
268
Growth Rate:
17.91%
Total runs:
1.4K
Run Growth:
-5
Growth Rate:
-0.37%
Total runs:
1.2K
Run Growth:
106
Growth Rate:
9.17%
Total runs:
1.0K
Run Growth:
1.0K
Growth Rate:
97.41%
Total runs:
1.0K
Run Growth:
127
Growth Rate:
12.37%
Total runs:
1.0K
Run Growth:
204
Growth Rate:
20.22%
Total runs:
973
Run Growth:
-29
Growth Rate:
-2.98%
Total runs:
917
Run Growth:
641
Growth Rate:
69.90%
Total runs:
904
Run Growth:
434
Growth Rate:
48.01%
Total runs:
761
Run Growth:
644
Growth Rate:
84.63%
Total runs:
715
Run Growth:
-10
Growth Rate:
-1.38%
Total runs:
698
Run Growth:
-131
Growth Rate:
-18.77%
Total runs:
681
Run Growth:
-9
Growth Rate:
-1.32%
Total runs:
678
Run Growth:
-80
Growth Rate:
-11.80%
Total runs:
627
Run Growth:
-136
Growth Rate:
-22.82%
Total runs:
617
Run Growth:
-811
Growth Rate:
-131.44%
Total runs:
518
Run Growth:
514
Growth Rate:
99.23%
Total runs:
518
Run Growth:
-674
Growth Rate:
-130.12%
Total runs:
472
Run Growth:
195
Growth Rate:
41.31%
Total runs:
442
Run Growth:
-117
Growth Rate:
-26.47%
Total runs:
400
Run Growth:
-742
Growth Rate:
-185.50%
Total runs:
385
Run Growth:
1
Growth Rate:
0.26%
Total runs:
362
Run Growth:
18
Growth Rate:
4.97%
Total runs:
355
Run Growth:
-1.3K
Growth Rate:
-366.76%
Total runs:
347
Run Growth:
-26
Growth Rate:
-7.49%