| Signal | Gemma 4 26B A4B | Delta | Qwen3.5-Flash |
|---|---|---|---|
Capabilities | 83 | -- | |
Benchmarks | 72 | +5 | |
Pricing | 100 | 0 | |
Context window size | 86 | -9 | |
Recency | 100 | -- | |
Output Capacity | 90 | +10 | |
| Overall Result | 2 wins | of 6 | 2 wins |
24
days higher
3
days
3
days higher
Alibaba
Qwen3.5-Flash saves you $13.50/month
That's $162.00/year compared to Gemma 4 26B A4B at your current usage level of 100K calls/month.
| Metric | Gemma 4 26B A4B | Qwen3.5-Flash | Winner |
|---|---|---|---|
| Overall Score | 73 | 69 | Gemma 4 26B A4B |
| Rank | #49 | #75 | Gemma 4 26B A4B |
| Quality Rank | #49 | #75 | Gemma 4 26B A4B |
| Adoption Rank | #49 | #75 | Gemma 4 26B A4B |
| Parameters | 26B | -- | -- |
| Context Window | 262K | 1000K | Qwen3.5-Flash |
| Pricing | $0.13/$0.40/M | $0.07/$0.26/M | -- |
| Signal Scores | |||
| Capabilities | 83 | 83 | Gemma 4 26B A4B |
| Benchmarks | 72 | 67 | Gemma 4 26B A4B |
| Pricing | 100 | 100 | Qwen3.5-Flash |
| Context window size | 86 | 95 | Qwen3.5-Flash |
| Recency | 100 | 100 | Gemma 4 26B A4B |
| Output Capacity | 90 | 80 | Gemma 4 26B A4B |
Our score (0-100) is driven by benchmark performance (90%) from Arena Elo ratings, MMLU, GPQA, HumanEval, SWE-bench, and 15+ standardized evaluations. Capabilities and context window serve as tiebreakers (10%). Here's what the scores mean for these two models:
Scores 73/100 (rank #49), placing it in the top 83% of all 290 models tracked.
Scores 69/100 (rank #75), placing it in the top 74% of all 290 models tracked.
With only a 4-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.
Qwen3.5-Flash offers 39% better value per quality point. At 1M tokens/day, you'd spend $4.88/month with Qwen3.5-Flash vs $7.95/month with Gemma 4 26B A4B - a $3.07 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 (73/100) 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
Gemma 4 26B A4B has a moderate advantage with a 4.200000000000003-point lead in composite score. It wins on more signal dimensions, but Qwen3.5-Flash has specific strengths that could make it the better choice for certain workflows.
Best for Quality
Gemma 4 26B A4B
Marginally better benchmark scores; both are excellent
Best for Cost
Qwen3.5-Flash
39% lower pricing; better value at scale
Best for Reliability
Gemma 4 26B A4B
Higher uptime and faster response speeds
Best for Prototyping
Gemma 4 26B A4B
Stronger community support and better developer experience
Best for Production
Gemma 4 26B A4B
Wider enterprise adoption and proven at scale
by Google
| Capability | Gemma 4 26B A4B | Qwen3.5-Flash |
|---|---|---|
| Vision (Image Input) | ||
| Function Calling | ||
| Streaming | ||
| JSON Mode | ||
| Reasoning | ||
| Web Search | ||
| Image Output |
Alibaba
Qwen3.5-Flash saves you $0.2850/month
That's 40% cheaper than Gemma 4 26B A4B 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 | Gemma 4 26B A4B | Qwen3.5-Flash |
|---|---|---|
| Context Window | 262K | 1M |
| Max Output Tokens | 262,144 | 65,536 |
| Open Source | Yes | No |
| Created | Apr 3, 2026 | Feb 25, 2026 |
Gemma 4 26B A4B scores 73/100 (rank #49) compared to Qwen3.5-Flash's 69/100 (rank #75), giving it a 4-point advantage. Gemma 4 26B A4B is the stronger overall choice, though Qwen3.5-Flash may excel in specific areas like cost efficiency.
Gemma 4 26B A4B is ranked #49 and Qwen3.5-Flash is ranked #75 out of 290+ AI models. Rankings use a composite score combining benchmark performance (90%) from MMLU, GPQA, HumanEval, SWE-bench, and 15+ standardized evaluations, with capabilities and context window as tiebreakers (10%). Scores update hourly.
Qwen3.5-Flash is cheaper at $0.26/M output tokens vs Gemma 4 26B A4B 's $0.40/M output tokens - 1.5x more expensive. Input token pricing: Gemma 4 26B A4B at $0.13/M vs Qwen3.5-Flash at $0.07/M.
Qwen3.5-Flash has a larger context window of 1,000,000 tokens compared to Gemma 4 26B A4B 's 262,144 tokens. A larger context window means the model can process longer documents and conversations.