LFM2.5-VL-1.6B Intelligence, Performance & Price Analysis
Model summary
Intelligence
Speed
Input Price
Output Price
Verbosity
LFM2.5-VL-1.6B is among the least intelligent models, but well priced when comparing to other open weight non-reasoning models of similar size. It's also notably fast, however somewhat verbose. The model supports text and image input, outputs text, and has a 32k tokens context window.
LFM2.5-VL-1.6B scores 6 on the Artificial Analysis Intelligence Index, placing it at the lower end among comparable models (averaging 8). When evaluating the Intelligence Index, it generated 8.2M tokens, which is somewhat verbose in comparison to the average of 7.0M.
Pricing for LFM2.5-VL-1.6B is $0.00 per 1M input tokens (competitively priced, average: $0.00) and $0.00 per 1M output tokens (competitively priced, average: $0.00). In total, it cost $0.00 to evaluate LFM2.5-VL-1.6B on the Intelligence Index.
At 435 tokens per second, LFM2.5-VL-1.6B is notably fast (249).
| Reasoning | No This page shows the non-reasoning version of this model. A reasoning variant may also exist. |
|---|---|
| Input modality | Supports: text, image |
| Output modality | Supports: text |
| Context window | 32k ~48 A4 pages of size 12 Arial font |
| Total parameters | 1.6B |
| License | lfm 1.0 |
| 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 coding & terminal use
Agentic tool use
Long context reasoning
Knowledge
1 - hallucination rate
Reasoning & knowledge
Scientific reasoning
Coding
Instruction following
Physics reasoning
Long-horizon agentic tasks
Kubernetes incident root-cause analysis
Visual reasoning
Openness
Artificial Analysis Openness Index: Score
Intelligence Index Comparisons
Intelligence vs. Price
Intelligence Index Token Use & Cost
Output Tokens Used to Run Artificial Analysis Intelligence Index
Cost to Run Artificial Analysis Intelligence Index
Context Window
Context Window
PricingUpdated
Pricing: Cache Hit, Input, and Output
Speed
Measured by Output Speed (tokens per second)
Output Speed
Output Speed vs. Price
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 LFM2.5-VL-1.6B
LFM2.5-VL-1.6B was released on January 5, 2026.
LFM2.5-VL-1.6B was created by Liquid AI.
LFM2.5-VL-1.6B scores 6 on the Artificial Analysis Intelligence Index, placing it at the lower end among other open weight non-reasoning models of similar size (median: 8).
LFM2.5-VL-1.6B generates output at 435.2 tokens per second (based on the median across providers serving the model), which is well above average compared to other open weight non-reasoning models of similar size (median: 249.1 t/s).
LFM2.5-VL-1.6B has a time to first token (TTFT) of 10.18s (based on the median across providers serving the model), which is at the higher end compared to other open weight non-reasoning models of similar size (median: 1.20s).
When evaluated on the Intelligence Index, LFM2.5-VL-1.6B generated 8.2M output tokens, which is somewhat higher than average compared to other open weight non-reasoning models of similar size (median: 7.0M).
No, LFM2.5-VL-1.6B is not a reasoning model. It provides direct responses without extended chain-of-thought reasoning.
LFM2.5-VL-1.6B supports text and image input.
LFM2.5-VL-1.6B supports text output.
Yes, LFM2.5-VL-1.6B supports image input and can analyze, describe, and answer questions about images.
Yes, LFM2.5-VL-1.6B is multimodal. It can process text and image input and generate text output.
LFM2.5-VL-1.6B has a context window of 32k tokens. This determines how much text and conversation history the model can process in a single request.
Yes, LFM2.5-VL-1.6B is open weights. The model weights are publicly available and can be downloaded for self-hosting.
LFM2.5-VL-1.6B has 1.6 billion parameters.
LFM2.5-VL-1.6B is released under the lfm 1.0 license. This license allows commercial use. View license
LFM2.5-VL-1.6B achieves a score of 6 on the Artificial Analysis Intelligence Index. This composite benchmark evaluates models across reasoning, knowledge, mathematics, and coding.
LFM2.5-VL-1.6B is an open weights model that can be self-hosted. View providers
LFM2.5-VL-1.6B is an open weights model that can be downloaded and self-hosted. Compare providers