Decision support

Qwen2.5 7B Instruct vs Llama-3.2-90B-Vision-Instruct

Compare canonical objects directly. The useful dimensions change with the object type, so model and hardware comparisons stay separate.

Benchmark results

Head to head on 2 benchmarks both models report

  • Qwen2.5 7B Instruct0leads
  • Llama-3.2-90B-Vision-Instruct2leads
  • Arena Vision

    Arena rating · Higher is better

    • Qwen2.5 7B Instruct
      Not reported
    • Llama-3.2-90B-Vision-Instruct
      1032
      Arena #148CI 1023 to 1042
    Runs and sources
    Qwen2.5 7B Instruct

    Not reported

    Llama-3.2-90B-Vision-Instruct
    • default103295% CI 1023 to 1042 · 8,682 votes
  • GPQA diamond

    Best published score · Higher is better

    • Qwen2.5 7B Instruct
      35.5%
      #153 of 161
    • Llama-3.2-90B-Vision-Instruct
      Best41.0%
      +5.6 pts ahead · #147 of 161
    Runs and sources
    Qwen2.5 7B Instruct
    • default35.5%
    Llama-3.2-90B-Vision-Instruct
    • default41.0%
  • OTIS Mock AIME 2024-2025

    Best published score · Higher is better

    • Qwen2.5 7B Instruct
      2.5%
      #152 of 158
    • Llama-3.2-90B-Vision-Instruct
      Best2.6%
      +0.1 pts ahead · #151 of 158
    Runs and sources
    Qwen2.5 7B Instruct
    • default2.5%
    Llama-3.2-90B-Vision-Instruct
    • default2.6%

Each model's best published result is shown; "Not reported" means no matched evaluation, not a score of zero. Arena and DeepSWE ranks are the leaderboards' own; other ranks are among catalogue models with a score. Results from different harnesses or settings are not directly comparable.

Benchmark compilation: Epoch AI, Capabilities & benchmarking (CC BY attribution). Scores are converted to percentages and model names matched to the Vertical Tabs catalog. Individual evaluations are credited to their original sources. External results may carry separate licences and evaluation configurations; do not interpret scores from different harnesses as directly comparable.

Arena ratings: Arena (lmarena-ai/leaderboard-dataset), licensed CC BY 4.0. Ratings come from pairwise human votes and are only comparable within one leaderboard; the interval is Arena's 95% confidence interval. Model names are matched to the Vertical Tabs catalog.

Model specifications

Release date
September 19, 2024
September 25, 2024
Context window
131K
128K
Native context
—
—
Max output tokens
8,192
4,096
Knowledge cutoff
—
2023-12
Open weights
Open weights
Open weights
Parameter count
7B
90B

API pricing · USD per 1M tokens

Input
—
—
Output
—
—
Cached input
—
—
Cache write
—
—

Capabilities and modalities

Input modalities
text
text, image
Output modalities
text
text
Tool calling
Supported
Supported
Reasoning option
—
—
Supported options
tools, temperature
tools, temperature
Capabilities
—
—

Architecture and availability

Architecture
—
—
Model families
—
—
Tokenizer
—
—
Instruction format
—
—
License
Apache 2.0
Llama 3.2 Community 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.

To give you the best experience, we use cookies for personalization, insights, and performance. Learn more.