| Signal | DeepSeek V3.2 | Delta | Llama 3 70B Instruct |
|---|---|---|---|
Capabilities | 67 | +50 | |
Benchmarks | 70 | +10 | |
Pricing | 100 | +0 | |
Context window size | 81 | +19 | |
Recency | 100 | +100 | |
Output Capacity | 80 | +15 | |
| Overall Result | 6 wins | of 6 | 0 wins |
Score History
70.3
current score
DeepSeek V3.2
right now
57
current score
DeepSeek
Meta
DeepSeek V3.2 saves you $43.90/month
That's $526.80/year compared to Llama 3 70B Instruct at your current usage level of 100K calls/month.
| Metric | DeepSeek V3.2 | Llama 3 70B Instruct | Winner |
|---|---|---|---|
| Overall Score | 70 | 57 | DeepSeek V3.2 |
| Rank | #98 | #157 | DeepSeek V3.2 |
| Quality Rank | #98 | #157 | DeepSeek V3.2 |
| Adoption Rank | #98 | #157 | DeepSeek V3.2 |
| Parameters | -- | 70B | -- |
| Context Window | 131K | 8K | DeepSeek V3.2 |
| Pricing | $0.25/$0.38/M | $0.51/$0.74/M | -- |
| Signal Scores | |||
| Capabilities | 67 | 17 | DeepSeek V3.2 |
| Benchmarks | 70 | 60 | DeepSeek V3.2 |
| Pricing | 100 | 99 | DeepSeek V3.2 |
| Context window size | 81 | 62 | DeepSeek V3.2 |
| Recency | 100 | 0 | DeepSeek V3.2 |
| Output Capacity | 80 | 65 | DeepSeek V3.2 |
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 70/100 (rank #98), placing it in the top 67% of all 290 models tracked.
Scores 57/100 (rank #157), placing it in the top 46% of all 290 models tracked.
DeepSeek V3.2 has a 13-point advantage, which typically translates to noticeably better performance on complex reasoning, code generation, and multi-step tasks.
DeepSeek V3.2 offers 50% better value per quality point. At 1M tokens/day, you'd spend $9.45/month with DeepSeek V3.2 vs $18.75/month with Llama 3 70B Instruct - a $9.30 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. DeepSeek V3.2 also offers lower per-token costs for high-volume support
Long document analysis
Larger context window (131K tokens) can process longer documents, contracts, and research papers in a single pass
Batch data extraction
Lower output pricing ($0.38/M) reduces costs when processing thousands of records daily
Creative writing & content
Higher overall composite score (70/100) correlates with better nuance, coherence, and style in long-form content
DeepSeek V3.2 clearly outperforms Llama 3 70B Instruct with a significant 13.299999999999997-point lead. For most general use cases, DeepSeek V3.2 is the stronger choice. However, Llama 3 70B Instruct may still excel in niche scenarios.
Best for Quality
DeepSeek V3.2
Marginally better benchmark scores; both are excellent
Best for Cost
DeepSeek V3.2
50% lower pricing; better value at scale
Best for Reliability
DeepSeek V3.2
Higher uptime and faster response speeds
Best for Prototyping
DeepSeek V3.2
Stronger community support and better developer experience
Best for Production
DeepSeek V3.2
Wider enterprise adoption and proven at scale
by DeepSeek
| Capability | DeepSeek V3.2 | Llama 3 70B Instruct |
|---|---|---|
| Vision (Image Input) | ||
| Function Callingdiffers | ||
| Streaming | ||
| JSON Modediffers | ||
| Reasoningdiffers | ||
| Web Search | ||
| Image Output |
DeepSeek
Meta
DeepSeek V3.2 saves you $0.8988/month
That's 50% cheaper than Llama 3 70B 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 | DeepSeek V3.2 | Llama 3 70B Instruct |
|---|---|---|
| Context Window | 131K | 8K |
| Max Output Tokens | 65,536 | 8,000 |
| Open Source | Yes | Yes |
| Created | Dec 1, 2025 | Apr 18, 2024 |