| Signal | Claude 3.5 Haiku | Delta | Llama 3.1 405B (base) |
|---|---|---|---|
Capabilities | 67 | +50 | |
Benchmarks | 71 | +71 | |
Pricing | 4 | -- | |
Context window size | 84 | +12 | |
Recency | 42 | +17 | |
Output Capacity | 65 | -10 | |
| Overall Result | 4 wins | of 6 | 1 wins |
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Anthropic
Meta
Claude 3.5 Haiku saves you $320.00/month
That's $3840.00/year compared to Llama 3.1 405B (base) at your current usage level of 100K calls/month.
| Metric | Claude 3.5 Haiku | Llama 3.1 405B (base) | Winner |
|---|---|---|---|
| Overall Score | 66 | 38 | Claude 3.5 Haiku |
| Rank | #162 | #283 | Claude 3.5 Haiku |
| Quality Rank | #162 | #283 | Claude 3.5 Haiku |
| Adoption Rank | #162 | #283 | Claude 3.5 Haiku |
| Parameters | -- | 405B | -- |
| Context Window | 200K | 33K | Claude 3.5 Haiku |
| Pricing | $0.80/$4.00/M | $4.00/$4.00/M | -- |
| Signal Scores | |||
| Capabilities | 67 | 17 | Claude 3.5 Haiku |
| Benchmarks | 71 | -- | Claude 3.5 Haiku |
| Pricing | 4 | 4 | Claude 3.5 Haiku |
| Context window size | 84 | 72 | Claude 3.5 Haiku |
| Recency | 42 | 25 | Claude 3.5 Haiku |
| Output Capacity | 65 | 75 | Llama 3.1 405B (base) |
Our composite score (0–100) combines six weighted signals: benchmark performance (25%), pricing efficiency (25%), context window size (15%), model recency (15%), output capacity (10%), and capability versatility (10%). Here's what the scores mean for these two models:
Scores 66/100 (rank #162), placing it in the top 44% of all 290 models tracked.
Scores 38/100 (rank #283), placing it in the top 3% of all 290 models tracked.
Claude 3.5 Haiku has a 27-point advantage, which typically translates to noticeably stronger performance on complex reasoning, code generation, and multi-step tasks.
Claude 3.5 Haiku offers 40% better value per quality point. At 1M tokens/day, you'd spend $72.00/month with Claude 3.5 Haiku vs $120.00/month with Llama 3.1 405B (base) — a $48.00 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
Higher benchmark score (0/100) indicates stronger performance on coding tasks like generating functions, debugging, and refactoring
Customer support chatbot
Faster response time (speed score 0/100) is critical for user-facing chat. Claude 3.5 Haiku also offers lower per-token costs for high-volume support
Long document analysis
Larger context window (200K tokens) can process longer documents, contracts, and research papers in a single pass
Batch data extraction
Lower output pricing ($4.00/M) reduces costs when processing thousands of records daily
Creative writing & content
Higher overall composite score (66/100) 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
Claude 3.5 Haiku clearly outperforms Llama 3.1 405B (base) with a significant 27.39999999999999-point lead. For most general use cases, Claude 3.5 Haiku is the stronger choice. However, Llama 3.1 405B (base) may still excel in niche scenarios.
Best for Quality
Claude 3.5 Haiku
Marginally better benchmark scores; both are excellent
Best for Cost
Claude 3.5 Haiku
40% lower pricing; better value at scale
Best for Reliability
Claude 3.5 Haiku
Higher uptime and faster response speeds
Best for Prototyping
Claude 3.5 Haiku
Stronger community support and better developer experience
Best for Production
Claude 3.5 Haiku
Wider enterprise adoption and proven at scale
by Anthropic
| Capability | Claude 3.5 Haiku | Llama 3.1 405B (base) |
|---|---|---|
| Vision (Image Input)differs | ||
| Function Callingdiffers | ||
| Streaming | ||
| JSON Mode | ||
| Reasoning | ||
| Web Searchdiffers | ||
| Image Output |
Anthropic
Meta
Claude 3.5 Haiku saves you $5.76/month
That's 48% cheaper than Llama 3.1 405B (base) 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 | Claude 3.5 Haiku | Llama 3.1 405B (base) |
|---|---|---|
| Context Window | 200K | 33K |
| Max Output Tokens | 8,192 | 32,768 |
| Open Source | Yes | Yes |
| Created | Nov 4, 2024 | Aug 2, 2024 |
Claude 3.5 Haiku scores 66/100 (rank #162) compared to Llama 3.1 405B (base)'s 38/100 (rank #283), giving it a 27-point advantage. Claude 3.5 Haiku is the stronger overall choice, though Llama 3.1 405B (base) may excel in specific areas like certain benchmarks.
Claude 3.5 Haiku is ranked #162 and Llama 3.1 405B (base) is ranked #283 out of 290+ AI models. Rankings use a composite score combining benchmark performance (25%), pricing (25%), context window (15%), recency (15%), output capacity (10%), and versatility (10%). Scores update hourly.
Claude 3.5 Haiku is cheaper at $4.00/M output tokens vs Llama 3.1 405B (base)'s $4.00/M output tokens — 1.0x more expensive. Input token pricing: Claude 3.5 Haiku at $0.80/M vs Llama 3.1 405B (base) at $4.00/M.
Claude 3.5 Haiku has a larger context window of 200,000 tokens compared to Llama 3.1 405B (base)'s 32,768 tokens. A larger context window means the model can process longer documents and conversations.