| Signal | Qwen2.5 Coder 7B Instruct | Delta | WizardLM-2 8x22B |
|---|---|---|---|
Capabilities | 33 | +17 | |
Benchmarks | 32 | +32 | |
Pricing | 100 | +1 | |
Context window size | 72 | -5 | |
Recency | 68 | +66 | |
Output Capacity | 20 | -45 | |
| Overall Result | 4 wins | of 6 | 2 wins |
Score History
34.3
current score
WizardLM-2 8x22B
right now
35.1
current score
Alibaba
Microsoft
Qwen2.5 Coder 7B Instruct saves you $85.50/month
That's $1026.00/year compared to WizardLM-2 8x22B at your current usage level of 100K calls/month.
| Metric | Qwen2.5 Coder 7B Instruct | WizardLM-2 8x22B | Winner |
|---|---|---|---|
| Overall Score | 34 | 35 | WizardLM-2 8x22B |
| Rank | #301 | #299 | WizardLM-2 8x22B |
| Quality Rank | #301 | #299 | WizardLM-2 8x22B |
| Adoption Rank | #301 | #299 | WizardLM-2 8x22B |
| Parameters | 7B | 22B | -- |
| Context Window | 33K | 66K | WizardLM-2 8x22B |
| Pricing | $0.03/$0.09/M | $0.62/$0.62/M | -- |
| Signal Scores | |||
| Capabilities | 33 | 17 | Qwen2.5 Coder 7B Instruct |
| Benchmarks | 32 | -- | Qwen2.5 Coder 7B Instruct |
| Pricing | 100 | 99 | Qwen2.5 Coder 7B Instruct |
| Context window size | 72 | 76 | WizardLM-2 8x22B |
| Recency | 68 | 2 | Qwen2.5 Coder 7B Instruct |
| Output Capacity | 20 | 65 | WizardLM-2 8x22B |
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 34/100 (rank #301), placing it in the top -3% of all 290 models tracked.
Scores 35/100 (rank #299), placing it in the top -3% of all 290 models tracked.
With only a 1-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.
Qwen2.5 Coder 7B Instruct offers 90% better value per quality point. At 1M tokens/day, you'd spend $1.80/month with Qwen2.5 Coder 7B Instruct vs $18.60/month with WizardLM-2 8x22B - a $16.80 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. Qwen2.5 Coder 7B Instruct 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 ($0.09/M) reduces costs when processing thousands of records daily
Creative writing & content
Higher overall composite score (35/100) correlates with better nuance, coherence, and style in long-form content
Qwen2.5 Coder 7B Instruct and WizardLM-2 8x22B are extremely close in overall performance (only 0.8000000000000043 points apart). Your best choice depends entirely on which specific strengths matter most for your use case.
Best for Quality
Qwen2.5 Coder 7B Instruct
Marginally better benchmark scores; both are excellent
Best for Cost
Qwen2.5 Coder 7B Instruct
90% lower pricing; better value at scale
Best for Reliability
Qwen2.5 Coder 7B Instruct
Higher uptime and faster response speeds
Best for Prototyping
Qwen2.5 Coder 7B Instruct
Stronger community support and better developer experience
Best for Production
Qwen2.5 Coder 7B Instruct
Wider enterprise adoption and proven at scale
by Alibaba
| Capability | Qwen2.5 Coder 7B Instruct | WizardLM-2 8x22B |
|---|---|---|
| Vision (Image Input) | ||
| Function Calling | ||
| Streaming | ||
| JSON Modediffers | ||
| Reasoning | ||
| Web Search | ||
| Image Output |
Alibaba
Microsoft
Qwen2.5 Coder 7B Instruct saves you $1.70/month
That's 91% cheaper than WizardLM-2 8x22B 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 7B Instruct | WizardLM-2 8x22B |
|---|---|---|
| Context Window | 33K | 66K |
| Max Output Tokens | -- | 8,000 |
| Open Source | Yes | Yes |
| Created | Apr 15, 2025 | Apr 16, 2024 |
WizardLM-2 8x22B scores 35/100 (rank #299) compared to Qwen2.5 Coder 7B Instruct's 34/100 (rank #301), giving it a 1-point advantage. WizardLM-2 8x22B is the stronger overall choice, though Qwen2.5 Coder 7B Instruct may excel in specific areas like cost efficiency.
Qwen2.5 Coder 7B Instruct is ranked #301 and WizardLM-2 8x22B is ranked #299 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.
Qwen2.5 Coder 7B Instruct is cheaper at $0.09/M output tokens vs WizardLM-2 8x22B's $0.62/M output tokens - 6.9x more expensive. Input token pricing: Qwen2.5 Coder 7B Instruct at $0.03/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 7B Instruct's 32,768 tokens. A larger context window means the model can process longer documents and conversations.