| Signal | Qwen2.5 Coder 32B Instruct | Delta | WizardLM-2 8x22B |
|---|---|---|---|
Capabilities | 17 | -- | |
Benchmarks | 46 | +46 | |
Pricing | 1 | +0 | |
Context window size | 72 | -5 | |
Recency | 42 | +38 | |
Output Capacity | 20 | -45 | |
| Overall Result | 3 wins | of 6 | 2 wins |
30
days ranked higher
0
days
0
days ranked higher
Alibaba
Microsoft
WizardLM-2 8x22B saves you $23.00/month
That's $276.00/year compared to Qwen2.5 Coder 32B Instruct at your current usage level of 100K calls/month.
| Metric | Qwen2.5 Coder 32B Instruct | WizardLM-2 8x22B | Winner |
|---|---|---|---|
| Overall Score | 42 | 32 | Qwen2.5 Coder 32B Instruct |
| Rank | #280 | #296 | Qwen2.5 Coder 32B Instruct |
| Quality Rank | #280 | #296 | Qwen2.5 Coder 32B Instruct |
| Adoption Rank | #280 | #296 | Qwen2.5 Coder 32B Instruct |
| Parameters | 32B | 22B | -- |
| Context Window | 33K | 66K | WizardLM-2 8x22B |
| Pricing | $0.66/$1.00/M | $0.62/$0.62/M | -- |
| Signal Scores | |||
| Capabilities | 17 | 17 | Qwen2.5 Coder 32B Instruct |
| Benchmarks | 46 | -- | Qwen2.5 Coder 32B Instruct |
| Pricing | 1 | 1 | Qwen2.5 Coder 32B Instruct |
| Context window size | 72 | 76 | WizardLM-2 8x22B |
| Recency | 42 | 4 | Qwen2.5 Coder 32B Instruct |
| Output Capacity | 20 | 65 | WizardLM-2 8x22B |
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 42/100 (rank #280), placing it in the top 4% of all 290 models tracked.
Scores 32/100 (rank #296), placing it in the top -2% of all 290 models tracked.
Qwen2.5 Coder 32B Instruct has a 10-point advantage, which typically translates to noticeably better performance on complex reasoning, code generation, and multi-step tasks.
WizardLM-2 8x22B offers 25% better value per quality point. At 1M tokens/day, you'd spend $18.60/month with WizardLM-2 8x22B vs $24.90/month with Qwen2.5 Coder 32B Instruct - a $6.30 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. WizardLM-2 8x22B also offers lower per-token costs for high-volume support
Long document analysis
Larger context window (66K tokens) can process longer documents, contracts, and research papers in a single pass
Batch data extraction
Lower output pricing ($0.62/M) reduces costs when processing thousands of records daily
Creative writing & content
Higher overall composite score (42/100) correlates with better nuance, coherence, and style in long-form content
Qwen2.5 Coder 32B Instruct clearly outperforms WizardLM-2 8x22B with a significant 10.299999999999997-point lead. For most general use cases, Qwen2.5 Coder 32B Instruct is the stronger choice. However, WizardLM-2 8x22B may still excel in niche scenarios.
Best for Quality
Qwen2.5 Coder 32B Instruct
Marginally better benchmark scores; both are excellent
Best for Cost
WizardLM-2 8x22B
25% lower pricing; better value at scale
Best for Reliability
Qwen2.5 Coder 32B Instruct
Higher uptime and faster response speeds
Best for Prototyping
Qwen2.5 Coder 32B Instruct
Stronger community support and better developer experience
Best for Production
Qwen2.5 Coder 32B Instruct
Wider enterprise adoption and proven at scale
by Alibaba
| Capability | Qwen2.5 Coder 32B Instruct | WizardLM-2 8x22B |
|---|---|---|
| Vision (Image Input) | ||
| Function Calling | ||
| Streaming | ||
| JSON Mode | ||
| Reasoning | ||
| Web Search | ||
| Image Output |
Alibaba
Microsoft
WizardLM-2 8x22B saves you $0.5280/month
That's 22% cheaper than Qwen2.5 Coder 32B Instruct 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 | Qwen2.5 Coder 32B Instruct | WizardLM-2 8x22B |
|---|---|---|
| Context Window | 33K | 66K |
| Max Output Tokens | -- | 8,000 |
| Open Source | Yes | Yes |
| Created | Nov 11, 2024 | Apr 16, 2024 |
Qwen2.5 Coder 32B Instruct scores 42/100 (rank #280) compared to WizardLM-2 8x22B's 32/100 (rank #296), giving it a 10-point advantage. Qwen2.5 Coder 32B Instruct is the stronger overall choice, though WizardLM-2 8x22B may excel in specific areas like cost efficiency.
Qwen2.5 Coder 32B Instruct is ranked #280 and WizardLM-2 8x22B is ranked #296 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.
WizardLM-2 8x22B is cheaper at $0.62/M output tokens vs Qwen2.5 Coder 32B Instruct's $1.00/M output tokens - 1.6x more expensive. Input token pricing: Qwen2.5 Coder 32B Instruct at $0.66/M vs WizardLM-2 8x22B at $0.62/M.
WizardLM-2 8x22B has a larger context window of 65,535 tokens compared to Qwen2.5 Coder 32B Instruct's 32,768 tokens. A larger context window means the model can process longer documents and conversations.