| Signal | ERNIE 4.5 300B A47B | Delta | Mercury |
|---|---|---|---|
Capabilities | 33 | -17 | |
Pricing | 1 | +0 | |
Context window size | 81 | 0 | |
Recency | 83 | +1 | |
Output Capacity | 68 | -7 | |
Benchmarks | 0 | -54 | |
| Overall Result | 2 wins | of 6 | 4 wins |
9
days higher
4
days
17
days higher
Baidu
Inception
Mercury saves you $20.50/month
That's $246.00/year compared to ERNIE 4.5 300B A47B at your current usage level of 100K calls/month.
| Metric | ERNIE 4.5 300B A47B | Mercury | Winner |
|---|---|---|---|
| Overall Score | 63 | 63 | Mercury |
| Rank | #210 | #208 | Mercury |
| Quality Rank | #210 | #208 | Mercury |
| Adoption Rank | #210 | #208 | Mercury |
| Parameters | 300B | -- | -- |
| Context Window | 123K | 128K | Mercury |
| Pricing | $0.28/$1.10/M | $0.25/$0.75/M | -- |
| Signal Scores | |||
| Capabilities | 33 | 50 | Mercury |
| Pricing | 1 | 1 | ERNIE 4.5 300B A47B |
| Context window size | 81 | 81 | Mercury |
| Recency | 83 | 83 | ERNIE 4.5 300B A47B |
| Output Capacity | 68 | 75 | Mercury |
| Benchmarks | -- | 55 | Mercury |
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 63/100 (rank #210), placing it in the top 28% of all 290 models tracked.
Scores 63/100 (rank #208), placing it in the top 29% 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.
Mercury offers 28% better value per quality point. At 1M tokens/day, you'd spend $15.00/month with Mercury vs $20.70/month with ERNIE 4.5 300B A47B - a $5.70 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. Mercury also offers lower per-token costs for high-volume support
Long document analysis
Larger context window (128K tokens) can process longer documents, contracts, and research papers in a single pass
Batch data extraction
Lower output pricing ($0.75/M) reduces costs when processing thousands of records daily
Creative writing & content
Higher overall composite score (63/100) correlates with better nuance, coherence, and style in long-form content
ERNIE 4.5 300B A47B and Mercury are extremely close in overall performance (only 0.10000000000000142 points apart). Your best choice depends entirely on which specific strengths matter most for your use case.
Best for Quality
ERNIE 4.5 300B A47B
Marginally better benchmark scores; both are excellent
Best for Cost
Mercury
28% lower pricing; better value at scale
Best for Reliability
ERNIE 4.5 300B A47B
Higher uptime and faster response speeds
Best for Prototyping
ERNIE 4.5 300B A47B
Stronger community support and better developer experience
Best for Production
ERNIE 4.5 300B A47B
Wider enterprise adoption and proven at scale
by Baidu
| Capability | ERNIE 4.5 300B A47B | Mercury |
|---|---|---|
| Vision (Image Input) | ||
| Function Callingdiffers | ||
| Streaming | ||
| JSON Mode | ||
| Reasoning | ||
| Web Search | ||
| Image Output |
Baidu
Inception
Mercury saves you $0.4740/month
That's 26% cheaper than ERNIE 4.5 300B A47B 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 | ERNIE 4.5 300B A47B | Mercury |
|---|---|---|
| Context Window | 123K | 128K |
| Max Output Tokens | 12,000 | 32,000 |
| Open Source | Yes | No |
| Created | Jun 30, 2025 | Jun 26, 2025 |
Mercury scores 63/100 (rank #208) compared to ERNIE 4.5 300B A47B 's 63/100 (rank #210), giving it a 0-point advantage. Mercury is the stronger overall choice, though ERNIE 4.5 300B A47B may excel in specific areas like certain benchmarks.
ERNIE 4.5 300B A47B is ranked #210 and Mercury is ranked #208 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.
Mercury is cheaper at $0.75/M output tokens vs ERNIE 4.5 300B A47B 's $1.10/M output tokens - 1.5x more expensive. Input token pricing: ERNIE 4.5 300B A47B at $0.28/M vs Mercury at $0.25/M.
Mercury has a larger context window of 128,000 tokens compared to ERNIE 4.5 300B A47B 's 123,000 tokens. A larger context window means the model can process longer documents and conversations.