| Signal | Jamba Large 1.7 | Delta | Qwen3 235B A22B |
|---|---|---|---|
Capabilities | 50 | -17 | |
Pricing | 8 | +6 | |
Context window size | 86 | +5 | |
Recency | 90 | +19 | |
Output Capacity | 60 | -5 | |
| Overall Result | 3 wins | of 5 | 2 wins |
11
days higher
1
days
18
days higher
AI21 Labs
Alibaba
Qwen3 235B A22B saves you $463.50/month
That's $5562.00/year compared to Jamba Large 1.7 at your current usage level of 100K calls/month.
| Metric | Jamba Large 1.7 | Qwen3 235B A22B | Winner |
|---|---|---|---|
| Overall Score | 71 | 71 | Qwen3 235B A22B |
| Rank | #158 | #157 | Qwen3 235B A22B |
| Quality Rank | #158 | #157 | Qwen3 235B A22B |
| Adoption Rank | #158 | #157 | Qwen3 235B A22B |
| Parameters | -- | 235B | -- |
| Context Window | 256K | 131K | Jamba Large 1.7 |
| Pricing | $2.00/$8.00/M | $0.45/$1.82/M | -- |
| Signal Scores | |||
| Capabilities | 50 | 67 | Qwen3 235B A22B |
| Pricing | 8 | 2 | Jamba Large 1.7 |
| Context window size | 86 | 81 | Jamba Large 1.7 |
| Recency | 90 | 72 | Jamba Large 1.7 |
| Output Capacity | 60 | 65 | Qwen3 235B A22B |
Our composite score (0–100) combines six weighted signals: benchmark performance (25%), pricing efficiency (25%), context window size (15%), model recency (15%), output capacity (10%), and capability versatility (10%). Here's what the scores mean for these two models:
Scores 71/100 (rank #158), placing it in the top 46% of all 290 models tracked.
Scores 71/100 (rank #157), placing it in the top 46% of all 290 models tracked.
With only a 0-point gap, these models are in the same performance tier. The practical difference in output quality is minimal - your choice should depend on pricing, latency requirements, and specific feature needs.
Qwen3 235B A22B offers 77% better value per quality point. At 1M tokens/day, you'd spend $34.13/month with Qwen3 235B A22B vs $150.00/month with Jamba Large 1.7 - a $115.88 monthly difference.
Both models have comparable response speeds. For most applications, the latency difference is negligible.
When latency matters most: Interactive chatbots, IDE code completion, real-time translation, and user-facing applications where response time directly impacts experience. For batch processing, background summarization, or offline analysis, latency is less critical.
Code generation & review
Higher benchmark score (0/100) indicates stronger performance on coding tasks like generating functions, debugging, and refactoring
Customer support chatbot
Faster response time (speed score 0/100) is critical for user-facing chat. Qwen3 235B A22B also offers lower per-token costs for high-volume support
Long document analysis
Larger context window (256K tokens) can process longer documents, contracts, and research papers in a single pass
Batch data extraction
Lower output pricing ($1.82/M) reduces costs when processing thousands of records daily
Creative writing & content
Higher overall composite score (71/100) correlates with better nuance, coherence, and style in long-form content
Jamba Large 1.7 and Qwen3 235B A22B are extremely close in overall performance (only 0.10000000000000853 points apart). Your best choice depends entirely on which specific strengths matter most for your use case.
Best for Quality
Jamba Large 1.7
Marginally better benchmark scores; both are excellent
Best for Cost
Qwen3 235B A22B
77% lower pricing; better value at scale
Best for Reliability
Jamba Large 1.7
Higher uptime and faster response speeds
Best for Prototyping
Jamba Large 1.7
Stronger community support and better developer experience
Best for Production
Jamba Large 1.7
Wider enterprise adoption and proven at scale
by AI21 Labs
| Capability | Jamba Large 1.7 | Qwen3 235B A22B |
|---|---|---|
| Vision (Image Input) | ||
| Function Calling | ||
| Streaming | ||
| JSON Mode | ||
| Reasoningdiffers | ||
| Web Search | ||
| Image Output |
AI21 Labs
Alibaba
Qwen3 235B A22B saves you $10.20/month
That's 77% cheaper than Jamba Large 1.7 at 1,000 tokens/request and 100 requests/day.
Assumes 60% input / 40% output token ratio per request. Actual costs may vary based on your usage pattern.
| Parameter | Jamba Large 1.7 | Qwen3 235B A22B |
|---|---|---|
| Context Window | 256K | 131K |
| Max Output Tokens | 4,096 | 8,192 |
| Open Source | Yes | Yes |
| Created | Aug 8, 2025 | Apr 28, 2025 |
Qwen3 235B A22B scores 71/100 (rank #157) compared to Jamba Large 1.7's 71/100 (rank #158), giving it a 0-point advantage. Qwen3 235B A22B is the stronger overall choice, though Jamba Large 1.7 may excel in specific areas like certain benchmarks.
Jamba Large 1.7 is ranked #158 and Qwen3 235B A22B is ranked #157 out of 290+ AI models. Rankings use a composite score combining benchmark performance (25%), pricing (25%), context window (15%), recency (15%), output capacity (10%), and versatility (10%). Scores update hourly.
Qwen3 235B A22B is cheaper at $1.82/M output tokens vs Jamba Large 1.7's $8.00/M output tokens - 4.4x more expensive. Input token pricing: Jamba Large 1.7 at $2.00/M vs Qwen3 235B A22B at $0.45/M.
Jamba Large 1.7 has a larger context window of 256,000 tokens compared to Qwen3 235B A22B's 131,072 tokens. A larger context window means the model can process longer documents and conversations.