| Signal | DeepSeek V3.2 | Delta | ERNIE 4.5 VL 28B A3B |
|---|---|---|---|
Capabilities | 67 | -- | |
Benchmarks | 70 | +70 | |
Pricing | 0 | 0 | |
Context window size | 83 | +12 | |
Recency | 100 | +9 | |
Output Capacity | 20 | -45 | |
| Overall Result | 3 wins | of 6 | 2 wins |
7
days higher
3
days
20
days higher
DeepSeek
Baidu
ERNIE 4.5 VL 28B A3B saves you $3.00/month
That's $36.00/year compared to DeepSeek V3.2 at your current usage level of 100K calls/month.
| Metric | DeepSeek V3.2 | ERNIE 4.5 VL 28B A3B | Winner |
|---|---|---|---|
| Overall Score | 74 | 75 | ERNIE 4.5 VL 28B A3B |
| Rank | #118 | #117 | ERNIE 4.5 VL 28B A3B |
| Quality Rank | #118 | #117 | ERNIE 4.5 VL 28B A3B |
| Adoption Rank | #118 | #117 | ERNIE 4.5 VL 28B A3B |
| Parameters | -- | 28B | -- |
| Context Window | 164K | 30K | DeepSeek V3.2 |
| Pricing | $0.26/$0.38/M | $0.14/$0.56/M | -- |
| Signal Scores | |||
| Capabilities | 67 | 67 | DeepSeek V3.2 |
| Benchmarks | 70 | -- | DeepSeek V3.2 |
| Pricing | 0 | 1 | ERNIE 4.5 VL 28B A3B |
| Context window size | 83 | 71 | DeepSeek V3.2 |
| Recency | 100 | 91 | DeepSeek V3.2 |
| Output Capacity | 20 | 65 | ERNIE 4.5 VL 28B A3B |
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 74/100 (rank #118), placing it in the top 60% of all 290 models tracked.
Scores 75/100 (rank #117), placing it in the top 60% of all 290 models tracked.
With only a 1-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.
DeepSeek V3.2 offers 9% better value per quality point. At 1M tokens/day, you'd spend $9.60/month with DeepSeek V3.2 vs $10.50/month with ERNIE 4.5 VL 28B A3B - a $0.90 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. DeepSeek V3.2 also offers lower per-token costs for high-volume support
Long document analysis
Larger context window (164K 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 (75/100) 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
DeepSeek V3.2 and ERNIE 4.5 VL 28B A3B are extremely close in overall performance (only 0.5 points apart). Your best choice depends entirely on which specific strengths matter most for your use case.
Best for Quality
DeepSeek V3.2
Marginally better benchmark scores; both are excellent
Best for Cost
DeepSeek V3.2
9% 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 | ERNIE 4.5 VL 28B A3B |
|---|---|---|
| Vision (Image Input)differs | ||
| Function Calling | ||
| Streaming | ||
| JSON Modediffers | ||
| Reasoning | ||
| Web Search | ||
| Image Output |
DeepSeek
Baidu
Assumes 60% input / 40% output token ratio per request. Actual costs may vary based on your usage pattern.
| Parameter | DeepSeek V3.2 | ERNIE 4.5 VL 28B A3B |
|---|---|---|
| Context Window | 164K | 30K |
| Max Output Tokens | -- | 8,000 |
| Open Source | Yes | Yes |
| Created | Dec 1, 2025 | Aug 12, 2025 |
ERNIE 4.5 VL 28B A3B scores 75/100 (rank #117) compared to DeepSeek V3.2's 74/100 (rank #118), giving it a 1-point advantage. ERNIE 4.5 VL 28B A3B is the stronger overall choice, though DeepSeek V3.2 may excel in specific areas like cost efficiency.
DeepSeek V3.2 is ranked #118 and ERNIE 4.5 VL 28B A3B is ranked #117 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.
DeepSeek V3.2 is cheaper at $0.38/M output tokens vs ERNIE 4.5 VL 28B A3B's $0.56/M output tokens - 1.5x more expensive. Input token pricing: DeepSeek V3.2 at $0.26/M vs ERNIE 4.5 VL 28B A3B at $0.14/M.
DeepSeek V3.2 has a larger context window of 163,840 tokens compared to ERNIE 4.5 VL 28B A3B's 30,000 tokens. A larger context window means the model can process longer documents and conversations.