| Signal | Llama 3.3 70B Instruct (free) | Delta | R1 |
|---|---|---|---|
Capabilities | 33 | -17 | |
Benchmarks | 71 | -2 | |
Pricing | 100 | +3 | |
Context window size | 76 | +0 | |
Recency | 38 | -8 | |
Output Capacity | 20 | -50 | |
| Overall Result | 2 wins | of 6 | 4 wins |
Score History
65.7
current score
R1
right now
73
current score
Meta
DeepSeek
Llama 3.3 70B Instruct (free) saves you $195.00/month
That's $2340.00/year compared to R1 at your current usage level of 100K calls/month.
| Metric | Llama 3.3 70B Instruct (free) | R1 | Winner |
|---|---|---|---|
| Overall Score | 66 | 73 | R1 |
| Rank | #124 | #76 | R1 |
| Quality Rank | #124 | #76 | R1 |
| Adoption Rank | #124 | #76 | R1 |
| Parameters | 70B | -- | -- |
| Context Window | 66K | 64K | Llama 3.3 70B Instruct (free) |
| Pricing | Free | $0.70/$2.50/M | -- |
| Signal Scores | |||
| Capabilities | 33 | 50 | R1 |
| Benchmarks | 71 | 73 | R1 |
| Pricing | 100 | 98 | Llama 3.3 70B Instruct (free) |
| Context window size | 76 | 76 | Llama 3.3 70B Instruct (free) |
| Recency | 38 | 46 | R1 |
| Output Capacity | 20 | 70 | 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 66/100 (rank #124), placing it in the top 58% of all 290 models tracked.
Scores 73/100 (rank #76), placing it in the top 74% of all 290 models tracked.
R1 has a 7-point advantage, which typically translates to noticeably better performance on complex reasoning, code generation, and multi-step tasks.
Compare the cost per quality point to find the best value for your specific workload.
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 (free) 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 ($0.00/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 has a moderate advantage with a 7.299999999999997-point lead in composite score. It wins on more signal dimensions, but Llama 3.3 70B Instruct (free) has specific strengths that could make it the better choice for certain workflows.
Best for Quality
Llama 3.3 70B Instruct (free)
Marginally better benchmark scores; both are excellent
Best for Cost
Llama 3.3 70B Instruct (free)
100% lower pricing; better value at scale
Best for Reliability
Llama 3.3 70B Instruct (free)
Higher uptime and faster response speeds
Best for Prototyping
Llama 3.3 70B Instruct (free)
Stronger community support and better developer experience
Best for Production
Llama 3.3 70B Instruct (free)
Wider enterprise adoption and proven at scale
by Meta
| Capability | Llama 3.3 70B Instruct (free) | R1 |
|---|---|---|
| Vision (Image Input) | ||
| Function Calling | ||
| Streaming | ||
| JSON Mode | ||
| Reasoningdiffers | ||
| Web Search | ||
| Image Output |
Meta
DeepSeek
Llama 3.3 70B Instruct (free) saves you $4.26/month
That's 100% 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 | Llama 3.3 70B Instruct (free) | R1 |
|---|---|---|
| Context Window | 66K | 64K |
| Max Output Tokens | -- | 16,000 |
| Open Source | Yes | Yes |
| Created | Dec 6, 2024 | Jan 20, 2025 |