| Signal | Mellum | Delta | Qwen3.5-Flash |
|---|---|---|---|
Capabilities | 17 | -67 | |
Pricing | 0 | 0 | |
Context window size | 0 | -95 | |
Recency | 80 | -20 | |
Output Capacity | 20 | -60 | |
Benchmarks | 0 | -67 | |
| Overall Result | 0 wins | of 6 | 6 wins |
0
days ranked higher
0
days
30
days ranked higher
JetBrains
Alibaba
Mellum saves you $19.50/month
That's $234.00/year compared to Qwen3.5-Flash at your current usage level of 100K calls/month.
| Metric | Mellum | Qwen3.5-Flash | Winner |
|---|---|---|---|
| Overall Score | 33 | 79 | Qwen3.5-Flash |
| Rank | #298 | #80 | Qwen3.5-Flash |
| Quality Rank | #298 | #80 | Qwen3.5-Flash |
| Adoption Rank | #298 | #80 | Qwen3.5-Flash |
| Parameters | -- | -- | -- |
| Context Window | -- | 1000K | -- |
| Pricing | Free | $0.07/$0.26/M | -- |
| Signal Scores | |||
| Capabilities | 17 | 83 | Qwen3.5-Flash |
| Pricing | 0 | 0 | Qwen3.5-Flash |
| Context window size | 0 | 95 | Qwen3.5-Flash |
| Recency | 80 | 100 | Qwen3.5-Flash |
| Output Capacity | 20 | 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 33/100 (rank #298), placing it in the top -2% 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 47-point advantage, which typically translates to noticeably stronger performance on complex reasoning, code generation, and multi-step tasks.
Compare the cost per quality point to find the best value for your specific workload.
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. Mellum 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 ($0.00/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 Mellum with a significant 46.7-point lead. For most general use cases, Qwen3.5-Flash is the stronger choice. However, Mellum may still excel in niche scenarios.
Best for Quality
Mellum
Marginally better benchmark scores; both are excellent
Best for Cost
Mellum
100% lower pricing; better value at scale
Best for Reliability
Mellum
Higher uptime and faster response speeds
Best for Prototyping
Mellum
Stronger community support and better developer experience
Best for Production
Mellum
Wider enterprise adoption and proven at scale
by JetBrains
| Capability | Mellum | Qwen3.5-Flash |
|---|---|---|
| Vision (Image Input)differs | ||
| Function Callingdiffers | ||
| Streaming | ||
| JSON Modediffers | ||
| Reasoningdiffers | ||
| Web Search | ||
| Image Output |
JetBrains
Alibaba
Mellum saves you $0.4290/month
That's 100% cheaper than Qwen3.5-Flash 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 | Mellum | Qwen3.5-Flash |
|---|---|---|
| Context Window | -- | 1M |
| Max Output Tokens | -- | 65,536 |
| Open Source | No | Yes |
| Created | Jun 1, 2025 | Feb 25, 2026 |
Qwen3.5-Flash scores 79/100 (rank #80) compared to Mellum's 33/100 (rank #298), giving it a 47-point advantage. Qwen3.5-Flash is the stronger overall choice, though Mellum may excel in specific areas like cost efficiency.
Mellum is ranked #298 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.
Mellum is cheaper at $0.00/M output tokens vs Qwen3.5-Flash's $0.26/M output tokens - 260.0x more expensive. Input token pricing: Mellum at $0.00/M vs Qwen3.5-Flash at $0.07/M.
Context window information is available on the individual model pages.