Battle of the Models

Compare specific LLM models, context windows, and capabilities.

No matches found
VS
No matches found

Llama 3.1 70B (via routing)

A-TIER

Requesty

Intelligence Score 87/100
Model Popularity 0 votes
Context Window 128K
Pricing Model Commercial / Paid
View Provider Analysis →

DeepSeek-V4 Flash

A-TIER

DeepSeek

Intelligence Score 83/100
Context Window 1M
Pricing Model Commercial / Paid
Model Popularity 0 votes
View Provider Analysis →
FINAL VERDICT

Llama 3.1 70B (via routing) Wins

With an intelligence score of 87/100 vs 83/100, Llama 3.1 70B (via routing) outperforms DeepSeek-V4 Flash by 4 points.

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

Detailed Comparison

Feature
Llama 3.1 70B (via routing)
DeepSeek-V4 Flash
Context Window
128K 1M
Architecture
Transformer (Open Weight) Dense Transformer
Est. MMLU Score
~80-84% ~75-79%
Release Date
Jul 2024 2024
Pricing Model
Paid / Commercial Paid / Commercial
Rate Limit (RPM)
60 RPM 60 RPM
Daily Limit
Credit-based Credit-based
Capabilities
No specific data
No specific data
Performance Tier
A-Tier (Excellent) B-Tier (Strong)
Speed Estimate
⚡ Fast ⚡ Very Fast
Primary Use Case
General Purpose ⚡ Fast Chat & Apps
Model Size
70B Undisclosed
Limitations
  • Requires underlying provider API keys
  • Free credit amount is limited
  • Routing adds minimal latency
  • 10M tokens is one-time only
  • API can be slow during peak hours (Chinese business hours)
  • Rate limiting during high demand periods
Key Strengths
  • AI Router: automatic provider failover
  • Prompt caching for cost savings
  • Multi-provider load balancing
  • DeepSeek-R1: OpenAI o1-level reasoning (open-source)
  • Mixture-of-Experts architecture for efficiency
  • OpenAI-compatible API (drop-in replacement)

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