Model Comparison

Comprehensive side-by-side analysis of model capabilities and performance

IBM

Granite 3.3 8B Instruct

IBM

Granite 3.3 8B Instruct is a multimodal language model developed by IBM. It achieves strong performance with an average score of 69.8% across 14 benchmarks. It excels particularly in HumanEval (89.7%), AttaQ (88.5%), HumanEval+ (86.1%). The model shows particular specialization in code tasks with an average performance of 78.3%. As a multimodal model, it can process and understand text, images, and other input formats seamlessly. It's licensed for commercial use, making it suitable for enterprise applications. Released in 2025, it represents IBM's latest advancement in AI technology.

Meta

Llama 3.1 70B Instruct

Meta

Llama 3.1 70B Instruct is a language model developed by Meta. It achieves strong performance with an average score of 74.7% across 18 benchmarks. It excels particularly in GSM-8K (CoT) (95.1%), ARC-C (94.8%), API-Bank (90.0%). It supports a 256K token context window for handling large documents. The model is available through 9 API providers. Released in 2024, it represents Meta's latest advancement in AI technology.

Meta

Llama 3.1 70B Instruct

Meta

2024-07-23

IBM

Granite 3.3 8B Instruct

IBM

2025-04-16

8 months newer

Performance Metrics

Context window and performance specifications

IBM

Granite 3.3 8B Instruct

Max Context:-
Parameters:8.0B
Meta

Llama 3.1 70B Instruct

Larger context
Max Context:256.0K
Parameters:70.0B

Average performance across 4 common benchmarks

IBM

Granite 3.3 8B Instruct

Average Score:72.4%
Meta

Llama 3.1 70B Instruct

+10.4%
Average Score:82.8%

Performance comparison across key benchmark categories

IBM

Granite 3.3 8B Instruct

math
75.0%
code
+2.0%
78.3%
general
63.9%
Meta

Llama 3.1 70B Instruct

math
+8.4%
83.3%
code
76.3%
general
+4.8%
68.7%
Benchmark Scores - Detailed View
Side-by-side comparison of all benchmark scores
Knowledge Cutoff
Training data recency comparison

Granite 3.3 8B Instruct

2024-04-01

More recent knowledge cutoff means awareness of newer technologies and frameworks

Provider Availability & Performance

Available providers and their performance metrics

IBM

Granite 3.3 8B Instruct

0 providers
Meta

Llama 3.1 70B Instruct

9 providers

Sambanova

Throughput: 74 tok/s
Latency: 0.5ms

Together

Throughput: 94 tok/s
Latency: 0.5ms

Hyperbolic

Throughput: 100 tok/s
Latency: 0.5ms

DeepInfra

Throughput: 25 tok/s
Latency: 0.5ms

Fireworks

Throughput: 32 tok/s
Latency: 0.5ms

Groq

Throughput: 250 tok/s
Latency: 0.5ms

Bedrock

Throughput: 100 tok/s
Latency: 0.5ms

Lambda

Throughput: 42 tok/s
Latency: 0.5ms

Cerebras

Throughput: 1204 tok/s
Latency: 0.2ms
IBM

Granite 3.3 8B Instruct

Avg Score:72.4%
Providers:0
Meta

Llama 3.1 70B Instruct

+10.4%
Avg Score:82.8%
Providers:9