Battle of the Models

Compare specific LLM models, context windows, and capabilities.

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VS
No matches found

DeepSeek Coder V2

A-TIER

Ollama

Intelligence Score 85/100
Model Popularity 0 votes
Context Window 64K tokens
Pricing Model Free / Open
View Provider Analysis →

LLaVA 1.5

A-TIER

llamafile

Intelligence Score 81/100
Context Window Local
Pricing Model Free / Open
Model Popularity 0 votes
View Provider Analysis →
FINAL VERDICT

DeepSeek Coder V2 Wins

With an intelligence score of 85/100 vs 81/100, DeepSeek Coder V2 outperforms LLaVA 1.5 by 4 points.

Close Match: The difference is minimal. Consider other factors like pricing and features.
HEAD-TO-HEAD

Detailed Comparison

Feature
DeepSeek Coder V2
LLaVA 1.5
Context Window
64K tokens Local
Architecture
Dense Transformer Transformer
Est. MMLU Score
~80-84% ~75-79%
Release Date
2024 2024
Pricing Model
Free Tier Free Tier
Rate Limit (RPM)
Hardware limited Hardware dependent
Daily Limit
Unlimited Unlimited
Capabilities
No specific data
Vision
Performance Tier
A-Tier (Excellent) B-Tier (Strong)
Speed Estimate
Medium Medium
Primary Use Case
💻 Code Generation General Purpose
Model Size
Undisclosed Undisclosed
Limitations
  • Depends on your RAM/GPU
  • Laptop fans will spin up
  • Large models (70B+) need heavy hardware
  • File sizes are large (contain weights)
  • CLI usage often required
  • Windows requires appending .exe
Key Strengths
  • Local Inference: Data never leaves your device
  • Modelfiles: Script your own system prompts
  • API: Local REST API for app integration
  • Executable weight files (multi-OS)
  • Integrated Web UI
  • OpenAI Compatible API server

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