Battle of the Models

Compare specific LLM models, context windows, and capabilities.

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mistralai/mistral-7b-instruct-v0.2

Replicate

Intelligence Score 76/100
Model Popularity 0 votes
Context Window 32K tokens
Pricing Model Commercial / Paid
View Provider Analysis →

DeepSeek: R1 Distill Llama 70B (free)

A-TIER

OpenRouter

Intelligence Score 83/100
Context Window 128k
Pricing Model Free / Open
Model Popularity 0 votes
View Provider Analysis →
FINAL VERDICT

DeepSeek: R1 Distill Llama 70B (free) Wins

With an intelligence score of 83/100 vs 76/100, DeepSeek: R1 Distill Llama 70B (free) outperforms mistralai/mistral-7b-instruct-v0.2 by 7 points.

HEAD-TO-HEAD

Detailed Comparison

Feature
mistralai/mistral-7b-instruct-v0.2
DeepSeek: R1 Distill Llama 70B (free)
Context Window
32K tokens 128k
Architecture
Transformer (Open Weight) Transformer (Open Weight)
Est. MMLU Score
~70-74% ~75-79%
Release Date
2024 2024
Pricing Model
Paid / Commercial Free Tier
Rate Limit (RPM)
Varies by model 20 requests/minute
Daily Limit
Credit-based 50 requests/day (up to 1000 with $10 topup)
Capabilities
No specific data
No specific data
Performance Tier
B-Tier (Strong) B-Tier (Strong)
Speed Estimate
⚡ Very Fast 🐢 Slower (Reasoning)
Primary Use Case
General Purpose 🧠 Complex Reasoning
Model Size
7b 70B
Limitations
  • Pay-per-second billing (can be expensive)
  • Cold starts for less popular models
  • Trial credits are minimal
  • Limits depend on account history/topup
  • Community key models
  • Free models have lower priority during peak demand
Key Strengths
  • Run any public model with an API
  • Fine-tune existing models easily
  • Cold boots can be slow for unpopular models
  • Unified API for 100+ models from all providers
  • OpenAI-compatible endpoint (drop-in replacement)
  • Automatic model fallback and routing

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