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 →

Qwen 2.5 VL 72B Instruct (free)

A-TIER

OpenRouter

Intelligence Score 83/100
Context Window 32k
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 83/100, DeepSeek Coder V2 outperforms Qwen 2.5 VL 72B Instruct (free) by 2 points.

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

Detailed Comparison

Feature
DeepSeek Coder V2
Qwen 2.5 VL 72B Instruct (free)
Context Window
64K tokens 32k
Architecture
Dense Transformer Transformer (Open Weight)
Est. MMLU Score
~80-84% ~75-79%
Release Date
2024 Sep-Nov 2024
Pricing Model
Free Tier Free Tier
Rate Limit (RPM)
Hardware limited 20 requests/minute
Daily Limit
Unlimited 50 requests/day (up to 1000 with $10 topup)
Capabilities
No specific data
No specific data
Performance Tier
A-Tier (Excellent) B-Tier (Strong)
Speed Estimate
Medium ⚡ Fast
Primary Use Case
💻 Code Generation 👁️ Vision & Multimodal
Model Size
Undisclosed 72B
Limitations
  • Depends on your RAM/GPU
  • Laptop fans will spin up
  • Large models (70B+) need heavy hardware
  • Limits depend on account history/topup
  • Community key models
  • Free models have lower priority during peak demand
Key Strengths
  • Local Inference: Data never leaves your device
  • Modelfiles: Script your own system prompts
  • API: Local REST API for app integration
  • Unified API for 100+ models from all providers
  • OpenAI-compatible endpoint (drop-in replacement)
  • Automatic model fallback and routing

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