| Signal | Grok 4.1 Fast | Delta | Qwen3.5-Flash |
|---|---|---|---|
Capabilities | 100 | +17 | |
Benchmarks | 76 | +9 | |
Pricing | 100 | 0 | |
Context window size | 100 | +5 | |
Recency | 100 | -- | |
Output Capacity | 75 | -6 | |
| Overall Result | 3 wins | of 6 | 2 wins |
Score History
78
current score
Grok 4.1 Fast
right now
68.7
current score
xAI
Alibaba
Qwen3.5-Flash saves you $25.50/month
That's $306.00/year compared to Grok 4.1 Fast at your current usage level of 100K calls/month.
| Metric | Grok 4.1 Fast | Qwen3.5-Flash | Winner |
|---|---|---|---|
| Overall Score | 78 | 69 | Grok 4.1 Fast |
| Rank | #52 | #109 | Grok 4.1 Fast |
| Quality Rank | #52 | #109 | Grok 4.1 Fast |
| Adoption Rank | #52 | #109 | Grok 4.1 Fast |
| Parameters | -- | -- | -- |
| Context Window | 2000K | 1000K | Grok 4.1 Fast |
| Pricing | $0.20/$0.50/M | $0.07/$0.26/M | -- |
| Signal Scores | |||
| Capabilities | 100 | 83 | Grok 4.1 Fast |
| Benchmarks | 76 | 66 | Grok 4.1 Fast |
| Pricing | 100 | 100 | Qwen3.5-Flash |
| Context window size | 100 | 95 | Grok 4.1 Fast |
| Recency | 100 | 100 | Grok 4.1 Fast |
| Output Capacity | 75 | 80 | Qwen3.5-Flash |
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%). Learn more about our methodology.
Scores 78/100 (rank #52), placing it in the top 82% of all 290 models tracked.
Scores 69/100 (rank #109), placing it in the top 63% of all 290 models tracked.
Grok 4.1 Fast has a 9-point advantage, which typically translates to noticeably better performance on complex reasoning, code generation, and multi-step tasks.
Qwen3.5-Flash offers 54% better value per quality point. At 1M tokens/day, you'd spend $4.88/month with Qwen3.5-Flash vs $10.50/month with Grok 4.1 Fast - a $5.63 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
Based on overall model capabilities and architecture for coding tasks like generating functions, debugging, and refactoring
Customer support chatbot
Suitable for user-facing chat with competitive response times. Qwen3.5-Flash 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 ($0.26/M) reduces costs when processing thousands of records daily
Creative writing & content
Higher overall composite score (78/100) 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
Grok 4.1 Fast has a moderate advantage with a 9.299999999999997-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
Grok 4.1 Fast
Marginally better benchmark scores; both are excellent
Best for Cost
Qwen3.5-Flash
54% lower pricing; better value at scale
Best for Reliability
Grok 4.1 Fast
Higher uptime and faster response speeds
Best for Prototyping
Grok 4.1 Fast
Stronger community support and better developer experience
Best for Production
Grok 4.1 Fast
Wider enterprise adoption and proven at scale
by xAI
| Capability | Grok 4.1 Fast | Qwen3.5-Flash |
|---|---|---|
| Vision (Image Input) | ||
| Function Calling | ||
| Streaming | ||
| JSON Mode | ||
| Reasoning | ||
| Web Searchdiffers | ||
| Image Output |
xAI
Alibaba
Qwen3.5-Flash saves you $0.5310/month
That's 55% cheaper than Grok 4.1 Fast 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 4.1 Fast | Qwen3.5-Flash |
|---|---|---|
| Context Window | 2M | 1M |
| Max Output Tokens | 30,000 | 65,536 |
| Open Source | No | No |
| Created | Nov 19, 2025 | Feb 25, 2026 |
For live coding scenarios requiring current API documentation or recent framework updates, Grok's web search and larger context window justify the premium - you're paying $0.50/M output tokens vs $0.26/M for capabilities that directly impact accuracy. The 15-point score gap (75 vs 60) suggests this pricing reflects genuine performance advantages, particularly when handling large codebases that exceed Qwen3.5-Flash's 1M token limit.
This reflects different architectural priorities - Qwen3.5-Flash appears optimized for generating extensive documentation or refactoring entire modules in single responses, while Grok 4.1 Fast's 30K limit suggests optimization for iterative development patterns. The score difference (75 vs 60) indicates Grok produces higher quality code within its output constraints, making it better for precision tasks rather than bulk generation.
Video input is largely irrelevant for coding tasks - the 15-point performance gap validates this, as Grok's web search directly enhances code quality by accessing current documentation. At $0.065/M input tokens (3x cheaper than Grok's $0.20/M), Qwen3.5-Flash's video capability feels like a misaligned feature tax for pure coding applications.
Monthly costs would be $3.65 for Qwen3.5-Flash vs $3.00 for Grok 4.1 Fast - surprisingly, the higher-performing model is cheaper overall despite 1.9x higher output pricing. With Grok ranking #1 vs #32 and scoring 25% higher (75 vs 60), you're essentially getting premium performance at a discount, making Qwen3.5-Flash hard to justify unless you specifically need 66K token outputs.
While both handle multilingual code, Qwen3.5-Flash's Alibaba heritage suggests potential advantages for Asian language comments and documentation - yet it still scores 15 points lower (60 vs 75) in overall coding benchmarks. The 2x context window advantage (2M vs 1M tokens) gives Grok more room to process extensive non-English documentation alongside code, likely offsetting any regional model biases.