| Signal | GPT-5.4 Nano | Delta | WizardLM-2 8x22B |
|---|---|---|---|
Capabilities | 100 | +83 | |
Benchmarks | 90 | +59 | |
Pricing | 99 | -1 | |
Context window size | 89 | +13 | |
Recency | 100 | +100 | |
Output Capacity | 85 | +20 | |
| Overall Result | 5 wins | of 6 | 1 wins |
Score History
79.3
current score
GPT-5.4 Nano
right now
28
current score
OpenAI
Microsoft
GPT-5.4 Nano saves you $10.50/month
That's $126.00/year compared to WizardLM-2 8x22B at your current usage level of 100K calls/month.
| Metric | GPT-5.4 Nano | WizardLM-2 8x22B | Winner |
|---|---|---|---|
| Overall Score | 79 | 28 | GPT-5.4 Nano |
| Rank | #42 | #335 | GPT-5.4 Nano |
| Quality Rank | #42 | #335 | GPT-5.4 Nano |
| Adoption Rank | #42 | #335 | GPT-5.4 Nano |
| Parameters | -- | 22B | -- |
| Context Window | 400K | 66K | GPT-5.4 Nano |
| Pricing | $0.20/$1.25/M | $0.62/$0.62/M | -- |
| Signal Scores | |||
| Capabilities | 100 | 17 | GPT-5.4 Nano |
| Benchmarks | 90 | 31 | GPT-5.4 Nano |
| Pricing | 99 | 99 | WizardLM-2 8x22B |
| Context window size | 89 | 76 | GPT-5.4 Nano |
| Recency | 100 | 0 | GPT-5.4 Nano |
| Output Capacity | 85 | 65 | GPT-5.4 Nano |
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 79/100 (rank #42), placing it in the top 86% of all 290 models tracked.
Scores 28/100 (rank #335), placing it in the top -15% of all 290 models tracked.
GPT-5.4 Nano has a 51-point advantage, which typically translates to noticeably stronger performance on complex reasoning, code generation, and multi-step tasks.
GPT-5.4 Nano offers 14% better value per quality point. At 1M tokens/day, you'd spend $18.60/month with WizardLM-2 8x22B vs $21.75/month with GPT-5.4 Nano - a $3.15 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 (400K 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 (79/100) 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
GPT-5.4 Nano clearly outperforms WizardLM-2 8x22B with a significant 51.3-point lead. For most general use cases, GPT-5.4 Nano is the stronger choice. However, WizardLM-2 8x22B may still excel in niche scenarios.
Best for Quality
GPT-5.4 Nano
Marginally better benchmark scores; both are excellent
Best for Cost
WizardLM-2 8x22B
14% lower pricing; better value at scale
Best for Reliability
GPT-5.4 Nano
Higher uptime and faster response speeds
Best for Prototyping
GPT-5.4 Nano
Stronger community support and better developer experience
Best for Production
GPT-5.4 Nano
Wider enterprise adoption and proven at scale
by OpenAI
| Capability | GPT-5.4 Nano | WizardLM-2 8x22B |
|---|---|---|
| Vision (Image Input)differs | ||
| Function Callingdiffers | ||
| Streaming | ||
| JSON Modediffers | ||
| Reasoningdiffers | ||
| Web Searchdiffers | ||
| Image Output |
OpenAI
Microsoft
Assumes 60% input / 40% output token ratio per request. Actual costs may vary based on your usage pattern.
| Parameter | GPT-5.4 Nano | WizardLM-2 8x22B |
|---|---|---|
| Context Window | 400K | 66K |
| Max Output Tokens | 128,000 | 8,000 |
| Open Source | No | Yes |
| Created | Mar 17, 2026 | Apr 16, 2024 |