| Signal | GPT-3.5 Turbo Instruct | Delta | WizardLM-2 8x22B |
|---|---|---|---|
Capabilities | 33 | -- | |
Pricing | 98 | -1 | |
Context window size | 52 | -17 | |
Recency | 0 | -- | |
Output Capacity | 60 | -5 | |
Benchmarks | 0 | -31 | |
| Overall Result | 0 wins | of 6 | 4 wins |
Score History
33.6
current score
GPT-3.5 Turbo Instruct
right now
28.5
current score
OpenAI
Microsoft
WizardLM-2 8x22B saves you $157.00/month
That's $1884.00/year compared to GPT-3.5 Turbo Instruct at your current usage level of 100K calls/month.
| Metric | GPT-3.5 Turbo Instruct | WizardLM-2 8x22B | Winner |
|---|---|---|---|
| Overall Score | 34 | 29 | GPT-3.5 Turbo Instruct |
| Rank | #306 | #312 | GPT-3.5 Turbo Instruct |
| Quality Rank | #306 | #312 | GPT-3.5 Turbo Instruct |
| Adoption Rank | #306 | #312 | GPT-3.5 Turbo Instruct |
| Parameters | -- | 22B | -- |
| Context Window | 4K | 66K | WizardLM-2 8x22B |
| Pricing | $1.50/$2.00/M | $0.62/$0.62/M | -- |
| Signal Scores | |||
| Capabilities | 33 | 33 | GPT-3.5 Turbo Instruct |
| Pricing | 98 | 99 | WizardLM-2 8x22B |
| Context window size | 52 | 69 | WizardLM-2 8x22B |
| Recency | 0 | 0 | GPT-3.5 Turbo Instruct |
| Output Capacity | 60 | 65 | WizardLM-2 8x22B |
| Benchmarks | -- | 31 | 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 #306), placing it in the top -5% of all 290 models tracked.
Scores 29/100 (rank #312), placing it in the top -7% of all 290 models tracked.
GPT-3.5 Turbo Instruct has a 5-point advantage, which typically translates to noticeably better performance on complex reasoning, code generation, and multi-step tasks.
WizardLM-2 8x22B offers 65% better value per quality point. At 1M tokens/day, you'd spend $18.60/month with WizardLM-2 8x22B vs $52.50/month with GPT-3.5 Turbo Instruct - a $33.90 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 (34/100) correlates with better nuance, coherence, and style in long-form content
GPT-3.5 Turbo Instruct has a moderate advantage with a 5.100000000000001-point lead in composite score. It wins on more signal dimensions, but WizardLM-2 8x22B has specific strengths that could make it the better choice for certain workflows.
Best for Quality
GPT-3.5 Turbo Instruct
Marginally better benchmark scores; both are excellent
Best for Cost
WizardLM-2 8x22B
65% lower pricing; better value at scale
Best for Reliability
GPT-3.5 Turbo Instruct
Higher uptime and faster response speeds
Best for Prototyping
GPT-3.5 Turbo Instruct
Stronger community support and better developer experience
Best for Production
GPT-3.5 Turbo Instruct
Wider enterprise adoption and proven at scale
by OpenAI
| Capability | GPT-3.5 Turbo Instruct | WizardLM-2 8x22B |
|---|---|---|
| Vision (Image Input) | ||
| Function Calling | ||
| Streaming | ||
| JSON Mode | ||
| Reasoning | ||
| Web Search | ||
| Image Output |
OpenAI
Microsoft
WizardLM-2 8x22B saves you $3.24/month
That's 64% cheaper than GPT-3.5 Turbo 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 | GPT-3.5 Turbo Instruct | WizardLM-2 8x22B |
|---|---|---|
| Context Window | 4K | 66K |
| Max Output Tokens | 4,096 | 8,000 |
| Open Source | No | Yes |
| Created | Sep 28, 2023 | Apr 16, 2024 |