The AI arena is free today

Open Superagent

North Micro Vision Instruct vs Parse

Comparing North Micro Vision Instruct and Parse across benchmarks, pricing, and capabilities.

Cohere · Cohere · Updated for 2026

Which is better?

North Micro Vision Instruct and Parse trade strengths across price, capabilities, and technical limits. The better choice depends on the workload.

Based on current LLM Stats indexes, shared benchmarks, pricing, and model metadata for 2026.

Choose North Micro Vision Instruct

  • you need open weights you can self-host or fine-tune

Choose Parse

  • you want the most recent training data — it shipped Aug 2026

At a glance

The differences that matter most.

North Micro Vision Instruct
Cohere
Parse
Cohere
Benchmark wins
—
—
Input price
— / M
— / M
Output price
— / M
— / M
Context window
—
8,192

Individual benchmarks

19 reported for North Micro Vision Instruct · 1 for Parse

No common benchmarks found

North Micro Vision Instruct and Parsedon't have any common benchmark datasets to compare. They may have been evaluated on different testing suites.

Human preference

Blind head-to-head votes and playground preference scores

Model Size

Parameter count comparison

100.0M diff

North Micro Vision Instruct has 0.1B more parameters than Parse, making it 4.3% larger.

Cohere
North Micro Vision Instruct
2.4Bparameters
Cohere
Parse
2.3Bparameters
2.4B
North Micro Vision Instruct
2.3B
Parse

Context Window

Maximum input and output token capacity

Only Parse specifies input context (8,192 tokens).

Cohere
North Micro Vision Instruct
Input- tokens
Output- tokens
Cohere
Parse
Input8,192 tokens
Output- tokens
Sat Sep 05 2026 • llm-stats.com

Input capabilities

Documented input modalities across available providers

Both North Micro Vision Instruct and Parse support multimodal inputs.

They are both capable of processing various types of data, offering versatility in application.

North Micro Vision Instruct

Text
Images
Audio
Video

Parse

Text
Images
Audio
Video

License

Usage and distribution terms

North Micro Vision Instruct is licensed under Apache 2.0, while Parse uses a proprietary license.

License differences may affect how you can use these models in commercial or open-source projects.

North Micro Vision Instruct

Apache 2.0

Open weights

Parse

Proprietary

Closed source

Release Timeline

When each model was launched

North Micro Vision Instruct was released on 2026-08-12, while Parse was released on 2026-08-27.

Parse is 1 month newer than North Micro Vision Instruct.

North Micro Vision Instruct

Aug 12, 2026

3 weeks ago

Parse

Aug 27, 2026

1 weeks ago

2w newer

Knowledge Cutoff

When training data ends

Neither model specifies a knowledge cutoff date.

Unable to compare the recency of their training data.

No cutoff dates available

Outputs Comparison

Notice missing or incorrect data?Start an Issue discussion→

Judge for yourself.

Run your own prompts against North Micro Vision Instruct and Parse side-by-side, then vote on the output you prefer.

North Micro Vision Instruct
✓ Preferred
Parse
Open in Playground

FAQ

Common questions about North Micro Vision Instruct vs Parse.

Which is better, North Micro Vision Instruct or Parse?

North Micro Vision Instruct (Cohere) and Parse (Cohere) each have strengths in different areas. Compare their benchmark scores, pricing, context windows, and capabilities above to determine which fits your needs.

How does North Micro Vision Instruct compare to Parse in benchmarks?

North Micro Vision Instruct scores DocVQA: 92.1%, ChartQA: 80.8%, OCRBench: 79.2%, AI2D: 77.5%, IFEval: 74.9%. Parse scores ParseBench: 79.2%.

What are the context window sizes for North Micro Vision Instruct and Parse?

North Micro Vision Instruct supports an unknown number of tokens and Parse supports 8K tokens. A larger context window lets you process longer documents, conversations, or codebases in a single request.

What are the main differences between North Micro Vision Instruct and Parse?

Key differences include licensing (Apache 2.0 vs Proprietary). See the full comparison above for benchmark-by-benchmark results.

Related comparisons