| Signal | DeepSeek V4 Pro | Delta | Llama 3.3 70B Instruct |
|---|---|---|---|
Capabilities | 67 | +17 | |
Benchmarks | 75 | +4 | |
Pricing | 99 | -1 | |
Context window size | 96 | +14 | |
Recency | 100 | +62 | |
Output Capacity | 93 | +23 | |
| Overall Result | 5 wins | of 6 | 1 wins |
Score History
75.7
current score
DeepSeek V4 Pro
right now
66.8
current score
DeepSeek
Meta
Llama 3.3 70B Instruct saves you $61.00/month
That's $732.00/year compared to DeepSeek V4 Pro at your current usage level of 100K calls/month.
| Metric | DeepSeek V4 Pro | Llama 3.3 70B Instruct | Winner |
|---|---|---|---|
| Overall Score | 76 | 67 | DeepSeek V4 Pro |
| Rank | #62 | #120 | DeepSeek V4 Pro |
| Quality Rank | #62 | #120 | DeepSeek V4 Pro |
| Adoption Rank | #62 | #120 | DeepSeek V4 Pro |
| Parameters | -- | 70B | -- |
| Context Window | 1049K | 131K | DeepSeek V4 Pro |
| Pricing | $0.43/$0.87/M | $0.10/$0.32/M | -- |
| Signal Scores | |||
| Capabilities | 67 | 50 | DeepSeek V4 Pro |
| Benchmarks | 75 | 71 | DeepSeek V4 Pro |
| Pricing | 99 | 100 | Llama 3.3 70B Instruct |
| Context window size | 96 | 81 | DeepSeek V4 Pro |
| Recency | 100 | 38 | DeepSeek V4 Pro |
| Output Capacity | 93 | 70 | DeepSeek V4 Pro |
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 76/100 (rank #62), placing it in the top 79% of all 290 models tracked.
Scores 67/100 (rank #120), placing it in the top 59% of all 290 models tracked.
DeepSeek V4 Pro has a 9-point advantage, which typically translates to noticeably better performance on complex reasoning, code generation, and multi-step tasks.
Llama 3.3 70B Instruct offers 68% better value per quality point. At 1M tokens/day, you'd spend $6.30/month with Llama 3.3 70B Instruct vs $19.58/month with DeepSeek V4 Pro - a $13.28 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. Llama 3.3 70B Instruct also offers lower per-token costs for high-volume support
Long document analysis
Larger context window (1049K tokens) can process longer documents, contracts, and research papers in a single pass
Batch data extraction
Lower output pricing ($0.32/M) reduces costs when processing thousands of records daily
Creative writing & content
Higher overall composite score (76/100) correlates with better nuance, coherence, and style in long-form content
DeepSeek V4 Pro has a moderate advantage with a 8.900000000000006-point lead in composite score. It wins on more signal dimensions, but Llama 3.3 70B Instruct has specific strengths that could make it the better choice for certain workflows.
Best for Quality
DeepSeek V4 Pro
Marginally better benchmark scores; both are excellent
Best for Cost
Llama 3.3 70B Instruct
68% lower pricing; better value at scale
Best for Reliability
DeepSeek V4 Pro
Higher uptime and faster response speeds
Best for Prototyping
DeepSeek V4 Pro
Stronger community support and better developer experience
Best for Production
DeepSeek V4 Pro
Wider enterprise adoption and proven at scale
by DeepSeek
| Capability | DeepSeek V4 Pro | Llama 3.3 70B Instruct |
|---|---|---|
| Vision (Image Input) | ||
| Function Calling | ||
| Streaming | ||
| JSON Mode | ||
| Reasoningdiffers | ||
| Web Search | ||
| Image Output |
DeepSeek
Meta
Llama 3.3 70B Instruct saves you $1.26/month
That's 69% cheaper than DeepSeek V4 Pro 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 | DeepSeek V4 Pro | Llama 3.3 70B Instruct |
|---|---|---|
| Context Window | 1.0M | 131K |
| Max Output Tokens | 384,000 | 16,384 |
| Open Source | Yes | Yes |
| Created | Apr 24, 2026 | Dec 6, 2024 |