Model Comparison

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

Jamba 1.5 Mini

AI21 Labs

Jamba 1.5 Mini is a language model developed by AI21 Labs. The model shows competitive results across 8 benchmarks. It excels particularly in ARC-C (85.7%), GSM8k (75.8%), MMLU (69.7%). It supports a 512K token context window for handling large documents. The model is available through 2 API providers. Released in 2024, it represents AI21 Labs's latest advancement in AI technology.

Alibaba

QwQ-32B-Preview

Alibaba

QwQ-32B-Preview is a language model developed by Alibaba. It achieves strong performance with an average score of 64.0% across 4 benchmarks. It excels particularly in MATH-500 (90.6%), GPQA (65.2%), AIME 2024 (50.0%). The model is available through 4 API providers. It's licensed for commercial use, making it suitable for enterprise applications. Released in 2024, it represents Alibaba's latest advancement in AI technology.

Jamba 1.5 Mini

AI21 Labs

2024-08-22

Alibaba

QwQ-32B-Preview

Alibaba

2024-11-28

3 months newer

Pricing Comparison

Cost per million tokens (USD)

Jamba 1.5 Mini

Input:$0.20
Output:$0.40
Alibaba

QwQ-32B-Preview

$0.25 cheaper
Input:$0.15
Output:$0.20

Performance Metrics

Context window and performance specifications

Jamba 1.5 Mini

Larger context
Max Context:512.3K
Parameters:52.0B
Alibaba

QwQ-32B-Preview

Max Context:65.5K
Parameters:32.5B

Average performance across 1 common benchmarks

Jamba 1.5 Mini

Average Score:32.3%
Alibaba

QwQ-32B-Preview

+32.9%
Average Score:65.2%

Performance comparison across key benchmark categories

Jamba 1.5 Mini

math
75.8%
general
46.6%
Alibaba

QwQ-32B-Preview

math
+14.8%
90.6%
general
+11.0%
57.6%
Benchmark Scores - Detailed View
Side-by-side comparison of all benchmark scores
Knowledge Cutoff
Training data recency comparison

Jamba 1.5 Mini

2024-03-05

QwQ-32B-Preview

2024-11-28

More recent knowledge cutoff means awareness of newer technologies and frameworks

Provider Availability & Performance

Available providers and their performance metrics

Jamba 1.5 Mini

2 providers

Google

Throughput: 100 tok/s
Latency: 0.3ms

Bedrock

Throughput: 100 tok/s
Latency: 0.5ms
Alibaba

QwQ-32B-Preview

4 providers

Together

Throughput: 62.14 tok/s
Latency: 0.74ms

Hyperbolic

Throughput: 31.9 tok/s
Latency: 1.05ms

DeepInfra

Throughput: 76.04 tok/s
Latency: 0.44ms

Fireworks

Throughput: 99.15 tok/s
Latency: 0.53ms

Jamba 1.5 Mini

Avg Score:32.3%
Providers:2
Alibaba

QwQ-32B-Preview

+32.9%
Avg Score:65.2%
Providers:4