| Signal | Hunyuan A13B Instruct | Delta | Llama 4 Scout |
|---|---|---|---|
Capabilities | 50 | -17 | |
Pricing | 1 | +0 | |
Context window size | 81 | -6 | |
Recency | 85 | +17 | |
Output Capacity | 85 | +15 | |
| Overall Result | 3 wins | of 5 | 2 wins |
9
days higher
5
days
16
days higher
Tencent
Meta
Llama 4 Scout saves you $19.50/month
That's $234.00/year compared to Hunyuan A13B Instruct at your current usage level of 100K calls/month.
| Metric | Hunyuan A13B Instruct | Llama 4 Scout | Winner |
|---|---|---|---|
| Overall Score | 72 | 72 | Hunyuan A13B Instruct |
| Rank | #147 | #149 | Hunyuan A13B Instruct |
| Quality Rank | #147 | #149 | Hunyuan A13B Instruct |
| Adoption Rank | #147 | #149 | Hunyuan A13B Instruct |
| Parameters | 13B | -- | -- |
| Context Window | 131K | 328K | Llama 4 Scout |
| Pricing | $0.14/$0.57/M | $0.08/$0.30/M | -- |
| Signal Scores | |||
| Capabilities | 50 | 67 | Llama 4 Scout |
| Pricing | 1 | 0 | Hunyuan A13B Instruct |
| Context window size | 81 | 88 | Llama 4 Scout |
| Recency | 85 | 68 | Hunyuan A13B Instruct |
| Output Capacity | 85 | 70 | Hunyuan A13B Instruct |
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 72/100 (rank #147), placing it in the top 50% of all 290 models tracked.
Scores 72/100 (rank #149), placing it in the top 49% of all 290 models tracked.
With only a 0-point gap, these models are in the same performance tier. The practical difference in output quality is minimal - your choice should depend on pricing, latency requirements, and specific feature needs.
Llama 4 Scout offers 46% better value per quality point. At 1M tokens/day, you'd spend $5.70/month with Llama 4 Scout vs $10.65/month with Hunyuan A13B Instruct - a $4.95 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. Llama 4 Scout also offers lower per-token costs for high-volume support
Long document analysis
Larger context window (328K tokens) can process longer documents, contracts, and research papers in a single pass
Batch data extraction
Lower output pricing ($0.30/M) reduces costs when processing thousands of records daily
Creative writing & content
Higher overall composite score (72/100) 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
Hunyuan A13B Instruct and Llama 4 Scout are extremely close in overall performance (only 0.30000000000001137 points apart). Your best choice depends entirely on which specific strengths matter most for your use case.
Best for Quality
Hunyuan A13B Instruct
Marginally better benchmark scores; both are excellent
Best for Cost
Llama 4 Scout
46% lower pricing; better value at scale
Best for Reliability
Hunyuan A13B Instruct
Higher uptime and faster response speeds
Best for Prototyping
Hunyuan A13B Instruct
Stronger community support and better developer experience
Best for Production
Hunyuan A13B Instruct
Wider enterprise adoption and proven at scale
by Tencent
| Capability | Hunyuan A13B Instruct | Llama 4 Scout |
|---|---|---|
| Vision (Image Input)differs | ||
| Function Callingdiffers | ||
| Streaming | ||
| JSON Mode | ||
| Reasoningdiffers | ||
| Web Search | ||
| Image Output |
Tencent
Meta
Llama 4 Scout saves you $0.4320/month
That's 46% cheaper than Hunyuan A13B 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 | Hunyuan A13B Instruct | Llama 4 Scout |
|---|---|---|
| Context Window | 131K | 328K |
| Max Output Tokens | 131,072 | 16,384 |
| Open Source | Yes | Yes |
| Created | Jul 8, 2025 | Apr 5, 2025 |
Hunyuan A13B Instruct scores 72/100 (rank #147) compared to Llama 4 Scout's 72/100 (rank #149), giving it a 0-point advantage. Hunyuan A13B Instruct is the stronger overall choice, though Llama 4 Scout may excel in specific areas like cost efficiency.
Hunyuan A13B Instruct is ranked #147 and Llama 4 Scout is ranked #149 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.
Llama 4 Scout is cheaper at $0.30/M output tokens vs Hunyuan A13B Instruct's $0.57/M output tokens - 1.9x more expensive. Input token pricing: Hunyuan A13B Instruct at $0.14/M vs Llama 4 Scout at $0.08/M.
Llama 4 Scout has a larger context window of 327,680 tokens compared to Hunyuan A13B Instruct's 131,072 tokens. A larger context window means the model can process longer documents and conversations.