| Signal | Grok 4.20 Multi-Agent Beta | Delta | Qwen3.5-27B |
|---|---|---|---|
Capabilities | 83 | -- | |
Pricing | 6 | +4 | |
Context window size | 100 | +14 | |
Recency | 100 | -- | |
Output Capacity | 20 | -60 | |
| Overall Result | 2 wins | of 5 | 1 wins |
0
days ranked higher
1
days
29
days ranked higher
xAI
Alibaba
Qwen3.5-27B saves you $402.50/month
That's $4830.00/year compared to Grok 4.20 Multi-Agent Beta at your current usage level of 100K calls/month.
| Metric | Grok 4.20 Multi-Agent Beta | Qwen3.5-27B | Winner |
|---|---|---|---|
| Overall Score | 81 | 87 | Qwen3.5-27B |
| Rank | #69 | #43 | Qwen3.5-27B |
| Quality Rank | #69 | #43 | Qwen3.5-27B |
| Adoption Rank | #69 | #43 | Qwen3.5-27B |
| Parameters | -- | 27B | -- |
| Context Window | 2000K | 262K | Grok 4.20 Multi-Agent Beta |
| Pricing | $2.00/$6.00/M | $0.20/$1.56/M | -- |
| Signal Scores | |||
| Capabilities | 83 | 83 | Grok 4.20 Multi-Agent Beta |
| Pricing | 6 | 2 | Grok 4.20 Multi-Agent Beta |
| Context window size | 100 | 86 | Grok 4.20 Multi-Agent Beta |
| Recency | 100 | 100 | Grok 4.20 Multi-Agent Beta |
| Output Capacity | 20 | 80 | Qwen3.5-27B |
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 81/100 (rank #69), placing it in the top 77% of all 290 models tracked.
Scores 87/100 (rank #43), placing it in the top 86% of all 290 models tracked.
Qwen3.5-27B has a 6-point advantage, which typically translates to noticeably better performance on complex reasoning, code generation, and multi-step tasks.
Qwen3.5-27B offers 78% better value per quality point. At 1M tokens/day, you'd spend $26.33/month with Qwen3.5-27B vs $120.00/month with Grok 4.20 Multi-Agent Beta — a $93.67 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. Qwen3.5-27B also offers lower per-token costs for high-volume support
Long document analysis
Larger context window (2000K tokens) can process longer documents, contracts, and research papers in a single pass
Batch data extraction
Lower output pricing ($1.56/M) reduces costs when processing thousands of records daily
Creative writing & content
Higher overall composite score (87/100) 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
Qwen3.5-27B has a moderate advantage with a 6.200000000000003-point lead in composite score. It wins on more signal dimensions, but Grok 4.20 Multi-Agent Beta has specific strengths that could make it the better choice for certain workflows.
Best for Quality
Grok 4.20 Multi-Agent Beta
Marginally better benchmark scores; both are excellent
Best for Cost
Qwen3.5-27B
78% lower pricing; better value at scale
Best for Reliability
Grok 4.20 Multi-Agent Beta
Higher uptime and faster response speeds
Best for Prototyping
Grok 4.20 Multi-Agent Beta
Stronger community support and better developer experience
Best for Production
Grok 4.20 Multi-Agent Beta
Wider enterprise adoption and proven at scale
by xAI
| Capability | Grok 4.20 Multi-Agent Beta | Qwen3.5-27B |
|---|---|---|
| Vision (Image Input) | ||
| Function Callingdiffers | ||
| Streaming | ||
| JSON Mode | ||
| Reasoning | ||
| Web Searchdiffers | ||
| Image Output |
xAI
Alibaba
Qwen3.5-27B saves you $8.58/month
That's 79% cheaper than Grok 4.20 Multi-Agent Beta 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 | Grok 4.20 Multi-Agent Beta | Qwen3.5-27B |
|---|---|---|
| Context Window | 2M | 262K |
| Max Output Tokens | -- | 65,536 |
| Open Source | No | Yes |
| Created | Mar 12, 2026 | Feb 25, 2026 |
Qwen3.5-27B scores 87/100 (rank #43) compared to Grok 4.20 Multi-Agent Beta's 81/100 (rank #69), giving it a 6-point advantage. Qwen3.5-27B is the stronger overall choice, though Grok 4.20 Multi-Agent Beta may excel in specific areas like certain benchmarks.
Grok 4.20 Multi-Agent Beta is ranked #69 and Qwen3.5-27B is ranked #43 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.
Qwen3.5-27B is cheaper at $1.56/M output tokens vs Grok 4.20 Multi-Agent Beta's $6.00/M output tokens — 3.8x more expensive. Input token pricing: Grok 4.20 Multi-Agent Beta at $2.00/M vs Qwen3.5-27B at $0.20/M.
Grok 4.20 Multi-Agent Beta has a larger context window of 2,000,000 tokens compared to Qwen3.5-27B's 262,144 tokens. A larger context window means the model can process longer documents and conversations.