Decision support
FastVLM 1.5B vs Sarvam-M
Compare canonical objects directly. The useful dimensions change with the object type, so model and hardware comparisons stay separate.
FastVLM 1.5B
Apple
Benchmark results
No benchmark results have been matched to these models yet.
Model specifications
Release date
May 7, 2025
May 20, 2025
Context window
—
33K
Native context
—
—
Max output tokens
—
32,768
Knowledge cutoff
—
—
Open weights
Open weights
Open weights
Parameter count
1.9B
23.6B
API pricing · USD per 1M tokens
Input
—
—
Output
—
—
Cached input
—
—
Cache write
—
—
Capabilities and modalities
Input modalities
text, image
text
Output modalities
text
text
Tool calling
—
—
Reasoning option
—
Supported
Supported options
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reasoning, temperature
Capabilities
—
—
Architecture and availability
Architecture
—
—
Model families
—
—
Tokenizer
—
—
Instruction format
—
—
License
apple-amlr
Apache 2.0
Providers
0
0
Provider endpoints
0
0
Ollama variants
0
0
Metadata source
curated
ai-research
A dash means the field is not reported. Provider-specific performance and pricing may differ.