Decision support
LFM3-1.7B vs Nex-N2.5-Pro
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
November 6, 2026
September 8, 2026
Context window
262K
262K
Native context
256K
—
Max output tokens
8,192
235,929
Knowledge cutoff
—
—
Open weights
Open weights
Open weights
Parameter count
1.7B
397B
API pricing · USD per 1M tokens
Input
$0.08
$0.075
Output
$0.20
$0.25
Cached input
$0.02
$0.015
Cache write
—
—
Capabilities and modalities
Input modalities
text
text, image
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
include_reasoning, logprobs, max_tokens, reasoning, reasoning_effort, structured_outputs, temperature, tool_choice, tools, top_k, top_logprobs, top_p
Capabilities
—
—
Architecture and availability
Architecture
—
—
Model families
—
—
Tokenizer
Other
Qwen3
Instruction format
—
—
License
—
—
Providers
1
1
Provider endpoints
1
1
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.