Decision support
LFM2.5-Embedding-350M vs Nemotron 3.5 Embed 1B
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 18, 2026
October 21, 2026
Context window
512
33K
Native context
—
—
Max output tokens
460
29,491
Knowledge cutoff
—
—
Open weights
Open weights
Open weights
Parameter count
350M
1B
API pricing · USD per 1M tokens
Input
$0.00
$0.00
Output
$0.00
$0.00
Cached input
—
—
Cache write
—
—
Capabilities and modalities
Input modalities
text
text, image
Output modalities
embeddings
embeddings
Tool calling
—
—
Reasoning option
—
—
Supported options
—
—
Capabilities
—
—
Architecture and availability
Architecture
—
—
Model families
—
—
Tokenizer
Other
Other
Instruction format
—
—
License
—
—
Providers
0
0
Provider endpoints
0
0
Ollama variants
0
0
Metadata source
ai-research
ai-research
A dash means the field is not reported. Provider-specific performance and pricing may differ.