Decision support
LFM2.5-2.6B vs Motif 3
Compare canonical objects directly. The useful dimensions change with the object type, so model and hardware comparisons stay separate.
Benchmark results
No benchmark results have been matched to these models yet.
Model specifications
Release date
August 11, 2026
August 7, 2026
Context window
128K
262K
Native context
128K
—
Max output tokens
8,192
235,929
Knowledge cutoff
—
—
Open weights
Open weights
Open weights
Parameter count
2.6B
315B
API pricing · USD per 1M tokens
Input
$0.35
$0.30
Output
$0.50
$1.20
Cached input
$0.04
$0.06
Cache write
—
—
Capabilities and modalities
Input modalities
text
text
Output modalities
text
text
Tool calling
Supported
Supported
Reasoning option
Supported
Supported
Supported options
frequency_penalty, include_reasoning, logprobs, max_completion_tokens, max_tokens, min_p, presence_penalty, reasoning, repetition_penalty, response_format, seed, stop, structured_outputs, temperature, tool_choice, tools, top_k, top_logprobs, top_p
frequency_penalty, include_reasoning, logprobs, max_tokens, presence_penalty, reasoning, repetition_penalty, response_format, structured_outputs, temperature, top_k, top_logprobs, top_p, tools
Capabilities
—
—
Architecture and availability
Architecture
—
—
Model families
—
—
Tokenizer
Other
Other
Instruction format
—
—
License
—
MIT
Providers
1
1
Provider endpoints
1
1
Ollama variants
7
0
Metadata source
ai-research
ai-research
A dash means the field is not reported. Provider-specific performance and pricing may differ.