ERNIE 4.5 VL 424B A47B vs Qwen3 30B-A3B Instruct 2507
Qwen3 30B-A3B Instruct 2507 comes out ahead, 57 to 44 on our weighted score, and it is the cheaper option too.
Baidu
ERNIE 4.5 VL 424B A47B
44/100- ECI—
- Price$0.42 / $1.25
- Context123K
- Our pick
Alibaba (Qwen)
Qwen3 30B-A3B Instruct 2507
57/100- ECI137.3
- Price$0.10 / $0.30
- Context262K
Add a model
Make it a three-way comparison.
Qwen3 30B-A3B Instruct 2507 is our pick
Qwen3 30B-A3B Instruct 2507 is the better all-round choice, scoring 57/100 against ERNIE 4.5 VL 424B A47B (44). It leads on price and context window. ERNIE 4.5 VL 424B A47B wins on inputs & features. The score weighs price 50%, inputs & features 30%, context window 20%. None of the shared benchmarks cover every model here yet, so capability is left out of this verdict.
- CapabilityNot enough dataNo independent benchmark covers every model here yet
- Lowest priceQwen3 30B-A3B Instruct 2507Qwen3 30B-A3B Instruct 2507 $0.15 · ERNIE 4.5 VL 424B A47B $0.627 per 1M tokens (3:1 blend)
- Longest contextQwen3 30B-A3B Instruct 2507Qwen3 30B-A3B Instruct 2507 262,144 · ERNIE 4.5 VL 424B A47B 123,000 tokens
- Widest inputsERNIE 4.5 VL 424B A47B ERNIE 4.5 VL 424B A47B : Text, Images · Qwen3 30B-A3B Instruct 2507: Text
- Self-hostingAll open weightsEvery model here can be downloaded and run on your own hardware
| Measure | Weight | ERNIE 4.5 VL 424B A47B | Qwen3 30B-A3B Instruct 2507 |
|---|---|---|---|
| Price | 50% | 57 | 85 |
| Inputs & features | 30% | 35 | 25 |
| Context window | 20% | 23 | 37 |
| Overall | 100% | 44/100 | 57/100 |
Left out because at least one model lacks the data: capability. The remaining weights were rescaled.
Every spec in one table
Highlighted cells lead their row. Dashes mean the data is not published.
| Specification | ||
|---|---|---|
| Capability | ||
| Capabilities Index (ECI) | — | 137.3 |
| ECI rank | — | #124 of 165 |
| GPQA DiamondGraduate-level science questions | — | 55.6% |
| OTIS Mock AIME 2024–2025Competition mathematics | — | 62.2% |
| Price per million tokens | ||
| Input | $0.42 | $0.10 (best) |
| Output | $1.25 | $0.30 (best) |
| Cached input | — | — |
| Blended (3:1) | $0.627 | $0.15 (best) |
| Long-context rate | Same rate | Same rate |
| Price source | Median of 1 providers | Median of 12 providers |
| Limits | ||
| Context window | 123,000 tokens | 262,144 tokens (best) |
| Max output | 16,000 tokens | 16,384 tokens (best) |
| Inputs and features | ||
| Text | Yes | Yes |
| Images | Yes | No |
| PDFs | No | No |
| Audio | No | No |
| Video | No | No |
| Reasoning | Yes | No |
| Tool calling | No | Yes |
| Structured output | No | No |
| Availability | ||
| Weights | Open | OpenApache 2.0 |
| API model ID | — | — |
| API providers | 1 | 14 (best) |
| Released | Jun 30, 2025 | Jul 28, 2025 |
| Knowledge cutoff | Mar 31, 2025 | — |
What would a month cost?
Enter your expected volume in millions of tokens. List prices only; caching and batch discounts would lower these.
ERNIE 4.5 VL 424B A47B $6.70
Qwen3 30B-A3B Instruct 2507$1.60
Which should you choose?
Which is better: ERNIE 4.5 VL 424B A47B or Qwen3 30B-A3B Instruct 2507?
Qwen3 30B-A3B Instruct 2507 is the better all-round choice, scoring 57/100 against ERNIE 4.5 VL 424B A47B (44). It leads on price and context window. ERNIE 4.5 VL 424B A47B wins on inputs & features. The score weighs price 50%, inputs & features 30%, context window 20%. None of the shared benchmarks cover every model here yet, so capability is left out of this verdict.
Which is cheaper, ERNIE 4.5 VL 424B A47B or Qwen3 30B-A3B Instruct 2507?
Qwen3 30B-A3B Instruct 2507 is cheaper at $0.10 input / $0.30 output per million tokens (median across 12 API providers). ERNIE 4.5 VL 424B A47B costs $0.42 input / $1.25 output per million tokens (median across 1 API provider). At a typical mix of three input tokens to one output token, that is $0.15 per million tokens for Qwen3 30B-A3B Instruct 2507 versus $0.627 for ERNIE 4.5 VL 424B A47B (4.2× as much).
Which scores higher on benchmarks?
There is no independent benchmark that covers both models yet. ERNIE 4.5 VL 424B A47B has not been scored yet and Qwen3 30B-A3B Instruct 2507 has an ECI of 137.3.
Which is better for coding?
There are no published SWE-bench Verified results for ERNIE 4.5 VL 424B A47B and Qwen3 30B-A3B Instruct 2507 yet, so there is no like-for-like coding score. Test both on a sample of your own tasks. Note that ERNIE 4.5 VL 424B A47B does not support tool calling, which most coding agents need.
Which has the bigger context window?
Qwen3 30B-A3B Instruct 2507 has the largest context window at 262,144 tokens, against 123,000 for ERNIE 4.5 VL 424B A47B . Maximum output per response: ERNIE 4.5 VL 424B A47B up to 16,000, Qwen3 30B-A3B Instruct 2507 up to 16,384 tokens.
Which can read images, PDFs, audio or video?
ERNIE 4.5 VL 424B A47B accepts text and images; Qwen3 30B-A3B Instruct 2507 accepts text. ERNIE 4.5 VL 424B A47B handles the widest range of inputs.
Are any of these open source?
Yes, both publish their weights (Apache 2.0), so you can self-host them.
Which is newer?
Qwen3 30B-A3B Instruct 2507 is the newest, released Jul 28, 2025. ERNIE 4.5 VL 424B A47B came out Jun 30, 2025. Knowledge cutoff: ERNIE 4.5 VL 424B A47B Mar 31, 2025.
How do you decide the winner?
Each model gets a 0–100 score on capability (50%, independent benchmark results); price (25%, blended price per million tokens (3 input : 1 output), log scale); inputs & features (15%, image, PDF, audio and video input, tool calling, structured output and reasoning); context window (10%, maximum tokens per request, log scale). Dimensions missing for any model are dropped and the remaining weights rescaled, so every model is judged on the same evidence. Specs and prices come from public model listings and the labs’ own API pages; capability scores come from independent benchmark runs. Data updated Nov 2, 2026.