Model Comparison

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

Jamba 1.5 Large

AI21 Labs

Jamba 1.5 Large is a language model developed by AI21 Labs. It achieves strong performance with an average score of 65.5% across 8 benchmarks. It excels particularly in ARC-C (93.0%), GSM8k (87.0%), MMLU (81.2%). 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.

Qwen3-235B-A22B-Thinking-2507

Alibaba Cloud / Qwen Team

Qwen3-235B-A22B-Thinking-2507 is a language model developed by Alibaba Cloud / Qwen Team. It achieves strong performance with an average score of 69.2% across 25 benchmarks. It excels particularly in MMLU-Redux (93.8%), AIME25 (92.3%), WritingBench (88.3%). It supports a 387K token context window for handling large documents. The model is available through 1 API provider. It's licensed for commercial use, making it suitable for enterprise applications. Released in 2025, it represents Alibaba Cloud / Qwen Team's latest advancement in AI technology.

Jamba 1.5 Large

AI21 Labs

2024-08-22

Qwen3-235B-A22B-Thinking-2507

Alibaba Cloud / Qwen Team

2025-07-25

11 months newer

Pricing Comparison

Cost per million tokens (USD)

Jamba 1.5 Large

Input:$2.00

Output:$8.00

Qwen3-235B-A22B-Thinking-2507

$6.70 cheaper

Input:$0.30

Output:$3.00

Performance Metrics

Context window and performance specifications

Jamba 1.5 Large

Larger context

Max Context:512.0K

Parameters:398.0B

Qwen3-235B-A22B-Thinking-2507

Max Context:387.1K

Parameters:235.0B

Average performance across 2 common benchmarks

Jamba 1.5 Large

Average Score:45.2%

Qwen3-235B-A22B-Thinking-2507

+37.5%

Average Score:82.8%

Performance comparison across key benchmark categories

Jamba 1.5 Large

factuality

58.3%

reasoning

+28.1%

93.0%

math

+26.9%

87.0%

general

57.1%

Qwen3-235B-A22B-Thinking-2507

factuality

+35.5%

93.8%

reasoning

64.9%

math

60.1%

general

+20.3%

77.4%

Benchmark Scores - Detailed View

Side-by-side comparison of all benchmark scores

Knowledge Cutoff

Training data recency comparison

Jamba 1.5 Large

2024-03-05

More recent knowledge cutoff means awareness of newer technologies and frameworks

Provider Availability & Performance

Available providers and their performance metrics

Jamba 1.5 Large

2 providers

Google

Throughput: 42 tok/s

Latency: 0.3ms

Bedrock

Throughput: 100 tok/s

Latency: 0.5ms

Qwen3-235B-A22B-Thinking-2507

1 providers

Novita

Jamba 1.5 Large

Avg Score:45.2%

Providers:2

Qwen3-235B-A22B-Thinking-2507

+37.5%

Avg Score:82.8%

Providers:1