| Signal | ERNIE 4.5 VL 424B A47B | Delta | Qwen3 235B A22B Thinking 2507 |
|---|---|---|---|
Capabilities | 50 | -17 | |
Pricing | 1 | 0 | |
Context window size | 81 | 0 | |
Recency | 83 | -5 | |
Output Capacity | 70 | +50 | |
| Overall Result | 1 wins | of 5 | 4 wins |
11
days higher
4
days
15
days higher
Baidu
Alibaba
Qwen3 235B A22B Thinking 2507 saves you $14.80/month
That's $177.60/year compared to ERNIE 4.5 VL 424B A47B at your current usage level of 100K calls/month.
| Metric | ERNIE 4.5 VL 424B A47B | Qwen3 235B A22B Thinking 2507 | Winner |
|---|---|---|---|
| Overall Score | 69 | 69 | ERNIE 4.5 VL 424B A47B |
| Rank | #168 | #169 | ERNIE 4.5 VL 424B A47B |
| Quality Rank | #168 | #169 | ERNIE 4.5 VL 424B A47B |
| Adoption Rank | #168 | #169 | ERNIE 4.5 VL 424B A47B |
| Parameters | 424B | 235B | -- |
| Context Window | 123K | 131K | Qwen3 235B A22B Thinking 2507 |
| Pricing | $0.42/$1.25/M | $0.15/$1.50/M | -- |
| Signal Scores | |||
| Capabilities | 50 | 67 | Qwen3 235B A22B Thinking 2507 |
| Pricing | 1 | 2 | Qwen3 235B A22B Thinking 2507 |
| Context window size | 81 | 81 | Qwen3 235B A22B Thinking 2507 |
| Recency | 83 | 88 | Qwen3 235B A22B Thinking 2507 |
| Output Capacity | 70 | 20 | ERNIE 4.5 VL 424B A47B |
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 69/100 (rank #168), placing it in the top 42% of all 290 models tracked.
Scores 69/100 (rank #169), placing it in the top 42% 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.
Both models are priced similarly, so the decision comes down to quality and features rather than cost.
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. ERNIE 4.5 VL 424B A47B also offers lower per-token costs for high-volume support
Long document analysis
Larger context window (131K tokens) can process longer documents, contracts, and research papers in a single pass
Batch data extraction
Lower output pricing ($1.25/M) reduces costs when processing thousands of records daily
Creative writing & content
Higher overall composite score (69/100) 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
ERNIE 4.5 VL 424B A47B and Qwen3 235B A22B Thinking 2507 are extremely close in overall performance (only 0.19999999999998863 points apart). Your best choice depends entirely on which specific strengths matter most for your use case.
Best for Quality
ERNIE 4.5 VL 424B A47B
Marginally better benchmark scores; both are excellent
Best for Cost
Qwen3 235B A22B Thinking 2507
2% lower pricing; better value at scale
Best for Reliability
ERNIE 4.5 VL 424B A47B
Higher uptime and faster response speeds
Best for Prototyping
ERNIE 4.5 VL 424B A47B
Stronger community support and better developer experience
Best for Production
ERNIE 4.5 VL 424B A47B
Wider enterprise adoption and proven at scale
by Baidu
| Capability | ERNIE 4.5 VL 424B A47B | Qwen3 235B A22B Thinking 2507 |
|---|---|---|
| Vision (Image Input)differs | ||
| Function Callingdiffers | ||
| Streaming | ||
| JSON Modediffers | ||
| Reasoning | ||
| Web Search | ||
| Image Output |
Baidu
Alibaba
Qwen3 235B A22B Thinking 2507 saves you $0.1929/month
That's 9% cheaper than ERNIE 4.5 VL 424B 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 VL 424B A47B | Qwen3 235B A22B Thinking 2507 |
|---|---|---|
| Context Window | 123K | 131K |
| Max Output Tokens | 16,000 | -- |
| Open Source | Yes | Yes |
| Created | Jun 30, 2025 | Jul 25, 2025 |
ERNIE 4.5 VL 424B A47B scores 69/100 (rank #168) compared to Qwen3 235B A22B Thinking 2507's 69/100 (rank #169), giving it a 0-point advantage. ERNIE 4.5 VL 424B A47B is the stronger overall choice, though Qwen3 235B A22B Thinking 2507 may excel in specific areas like certain benchmarks.
ERNIE 4.5 VL 424B A47B is ranked #168 and Qwen3 235B A22B Thinking 2507 is ranked #169 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.
ERNIE 4.5 VL 424B A47B is cheaper at $1.25/M output tokens vs Qwen3 235B A22B Thinking 2507's $1.50/M output tokens - 1.2x more expensive. Input token pricing: ERNIE 4.5 VL 424B A47B at $0.42/M vs Qwen3 235B A22B Thinking 2507 at $0.15/M.
Qwen3 235B A22B Thinking 2507 has a larger context window of 131,072 tokens compared to ERNIE 4.5 VL 424B A47B 's 123,000 tokens. A larger context window means the model can process longer documents and conversations.