| Signal | R1 | Delta | WizardLM-2 8x22B |
|---|---|---|---|
Capabilities | 50 | +33 | |
Benchmarks | 73 | +42 | |
Pricing | 98 | -2 | |
Context window size | 76 | 0 | |
Recency | 46 | +46 | |
Output Capacity | 70 | +5 | |
| Overall Result | 4 wins | of 6 | 2 wins |
Score History
73
current score
R1
right now
28
current score
DeepSeek
Microsoft
WizardLM-2 8x22B saves you $102.00/month
That's $1224.00/year compared to R1 at your current usage level of 100K calls/month.
| Metric | R1 | WizardLM-2 8x22B | Winner |
|---|---|---|---|
| Overall Score | 73 | 28 | R1 |
| Rank | #76 | #335 | R1 |
| Quality Rank | #76 | #335 | R1 |
| Adoption Rank | #76 | #335 | R1 |
| Parameters | -- | 22B | -- |
| Context Window | 64K | 66K | WizardLM-2 8x22B |
| Pricing | $0.70/$2.50/M | $0.62/$0.62/M | -- |
| Signal Scores | |||
| Capabilities | 50 | 17 | R1 |
| Benchmarks | 73 | 31 | R1 |
| Pricing | 98 | 99 | WizardLM-2 8x22B |
| Context window size | 76 | 76 | WizardLM-2 8x22B |
| Recency | 46 | 0 | R1 |
| Output Capacity | 70 | 65 | R1 |
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 73/100 (rank #76), placing it in the top 74% of all 290 models tracked.
Scores 28/100 (rank #335), placing it in the top -15% of all 290 models tracked.
R1 has a 45-point advantage, which typically translates to noticeably stronger performance on complex reasoning, code generation, and multi-step tasks.
R1 offers 61% better value per quality point. At 1M tokens/day, you'd spend $18.60/month with WizardLM-2 8x22B vs $48.00/month with R1 - a $29.40 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. 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 (73/100) correlates with better nuance, coherence, and style in long-form content
R1 clearly outperforms WizardLM-2 8x22B with a significant 45-point lead. For most general use cases, R1 is the stronger choice. However, WizardLM-2 8x22B may still excel in niche scenarios.
Best for Quality
R1
Marginally better benchmark scores; both are excellent
Best for Cost
WizardLM-2 8x22B
61% lower pricing; better value at scale
Best for Reliability
R1
Higher uptime and faster response speeds
Best for Prototyping
R1
Stronger community support and better developer experience
Best for Production
R1
Wider enterprise adoption and proven at scale
by DeepSeek
| Capability | R1 | WizardLM-2 8x22B |
|---|---|---|
| Vision (Image Input) | ||
| Function Callingdiffers | ||
| Streaming | ||
| JSON Mode | ||
| Reasoningdiffers | ||
| Web Search | ||
| Image Output |
DeepSeek
Microsoft
WizardLM-2 8x22B saves you $2.40/month
That's 56% cheaper than R1 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 | R1 | WizardLM-2 8x22B |
|---|---|---|
| Context Window | 64K | 66K |
| Max Output Tokens | 16,000 | 8,000 |
| Open Source | Yes | Yes |
| Created | Jan 20, 2025 | Apr 16, 2024 |