| Signal | Llemma 7b | Delta | Qwen3.5-Flash |
|---|---|---|---|
Capabilities | 17 | -67 | |
Pricing | 1 | +1 | |
Context window size | 57 | -38 | |
Recency | 71 | -29 | |
Output Capacity | 60 | -20 | |
Benchmarks | 0 | -67 | |
| Overall Result | 1 wins | of 6 | 5 wins |
0
days ranked higher
0
days
30
days ranked higher
eleutherai
Alibaba
Qwen3.5-Flash saves you $120.50/month
That's $1446.00/year compared to Llemma 7b at your current usage level of 100K calls/month.
| Metric | Llemma 7b | Qwen3.5-Flash | Winner |
|---|---|---|---|
| Overall Score | 48 | 79 | Qwen3.5-Flash |
| Rank | #269 | #80 | Qwen3.5-Flash |
| Quality Rank | #269 | #80 | Qwen3.5-Flash |
| Adoption Rank | #269 | #80 | Qwen3.5-Flash |
| Parameters | 7B | -- | -- |
| Context Window | 4K | 1000K | Qwen3.5-Flash |
| Pricing | $0.80/$1.20/M | $0.07/$0.26/M | -- |
| Signal Scores | |||
| Capabilities | 17 | 83 | Qwen3.5-Flash |
| Pricing | 1 | 0 | Llemma 7b |
| Context window size | 57 | 95 | Qwen3.5-Flash |
| Recency | 71 | 100 | Qwen3.5-Flash |
| Output Capacity | 60 | 80 | Qwen3.5-Flash |
| Benchmarks | -- | 67 | Qwen3.5-Flash |
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 48/100 (rank #269), placing it in the top 8% of all 290 models tracked.
Scores 79/100 (rank #80), placing it in the top 73% of all 290 models tracked.
Qwen3.5-Flash has a 32-point advantage, which typically translates to noticeably stronger performance on complex reasoning, code generation, and multi-step tasks.
Qwen3.5-Flash offers 84% better value per quality point. At 1M tokens/day, you'd spend $4.88/month with Qwen3.5-Flash vs $30.00/month with Llemma 7b - a $25.13 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. Qwen3.5-Flash also offers lower per-token costs for high-volume support
Long document analysis
Larger context window (1000K tokens) can process longer documents, contracts, and research papers in a single pass
Batch data extraction
Lower output pricing ($0.26/M) reduces costs when processing thousands of records daily
Creative writing & content
Higher overall composite score (79/100) correlates with better nuance, coherence, and style in long-form content
Image understanding & OCR
Supports vision input - can analyze screenshots, diagrams, photos, and scanned documents directly
Qwen3.5-Flash clearly outperforms Llemma 7b with a significant 31.900000000000006-point lead. For most general use cases, Qwen3.5-Flash is the stronger choice. However, Llemma 7b may still excel in niche scenarios.
Best for Quality
Llemma 7b
Marginally better benchmark scores; both are excellent
Best for Cost
Qwen3.5-Flash
84% lower pricing; better value at scale
Best for Reliability
Llemma 7b
Higher uptime and faster response speeds
Best for Prototyping
Llemma 7b
Stronger community support and better developer experience
Best for Production
Llemma 7b
Wider enterprise adoption and proven at scale
by eleutherai
| Capability | Llemma 7b | Qwen3.5-Flash |
|---|---|---|
| Vision (Image Input)differs | ||
| Function Callingdiffers | ||
| Streaming | ||
| JSON Modediffers | ||
| Reasoningdiffers | ||
| Web Search | ||
| Image Output |
eleutherai
Alibaba
Qwen3.5-Flash saves you $2.45/month
That's 85% cheaper than Llemma 7b 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 | Llemma 7b | Qwen3.5-Flash |
|---|---|---|
| Context Window | 4K | 1M |
| Max Output Tokens | 4,096 | 65,536 |
| Open Source | Yes | No |
| Created | Apr 14, 2025 | Feb 25, 2026 |
Qwen3.5-Flash scores 79/100 (rank #80) compared to Llemma 7b's 48/100 (rank #269), giving it a 32-point advantage. Qwen3.5-Flash is the stronger overall choice, though Llemma 7b may excel in specific areas like certain benchmarks.
Llemma 7b is ranked #269 and Qwen3.5-Flash is ranked #80 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.
Qwen3.5-Flash is cheaper at $0.26/M output tokens vs Llemma 7b's $1.20/M output tokens - 4.6x more expensive. Input token pricing: Llemma 7b at $0.80/M vs Qwen3.5-Flash at $0.07/M.
Qwen3.5-Flash has a larger context window of 1,000,000 tokens compared to Llemma 7b's 4,096 tokens. A larger context window means the model can process longer documents and conversations.