Qwen Flash vs Qwen3 30B-A3B Instruct 2507 vs ERNIE 4.5 21B A3B
Qwen Flash comes out ahead, 69 to 57 and 57 on our weighted score, though ERNIE 4.5 21B A3B is 11% cheaper per token.
- Our pick
Alibaba (Qwen)
Qwen Flash
69/100- ECI—
- Price$0.05 / $0.40
- Context1M
Alibaba (Qwen)
Qwen3 30B-A3B Instruct 2507
57/100- ECI137.3
- Price$0.10 / $0.30
- Context262K
Baidu
ERNIE 4.5 21B A3B
57/100- ECI—
- Price$0.07 / $0.28
- Context131K
Qwen Flash is our pick
Qwen Flash is the better all-round choice, scoring 69/100 against Qwen3 30B-A3B Instruct 2507 (57) and ERNIE 4.5 21B A3B (57). It leads on inputs & features and context window. ERNIE 4.5 21B A3B wins on price. 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 priceERNIE 4.5 21B A3BERNIE 4.5 21B A3B $0.122 · Qwen Flash $0.138 · Qwen3 30B-A3B Instruct 2507 $0.15 per 1M tokens (3:1 blend)
- Longest contextQwen FlashQwen Flash 1,000,000 · Qwen3 30B-A3B Instruct 2507 262,144 · ERNIE 4.5 21B A3B 131,072 tokens
- Widest inputsSame inputsQwen Flash: Text · Qwen3 30B-A3B Instruct 2507: Text · ERNIE 4.5 21B A3B: Text
- Self-hostingQwen3 30B-A3B Instruct 2507 and ERNIE 4.5 21B A3BPublishes downloadable weights (Apache 2.0 and Apache-2.0)
| Measure | Weight | Qwen Flash | Qwen3 30B-A3B Instruct 2507 | ERNIE 4.5 21B A3B |
|---|---|---|---|---|
| Price | 50% | 87 | 85 | 89 |
| Inputs & features | 30% | 45 | 25 | 25 |
| Context window | 20% | 60 | 37 | 25 |
| Overall | 100% | 69/100 | 57/100 | 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 | $0.05 (best) | $0.10 | $0.07 |
| Output | $0.40 | $0.30 | $0.28 (best) |
| Cached input | $0.01 | — | — |
| Blended (3:1) | $0.138 | $0.15 | $0.122 (best) |
| Long-context rate | Over 256K: $0.25 / $2.00 | Same rate | Same rate |
| Price source | Official Alibaba API | Median of 12 providers | Median of 1 providers |
| Limits | |||
| Context window | 1,000,000 tokens (best) | 262,144 tokens | 131,072 tokens |
| Max output | 32,768 tokens (best) | 16,384 tokens | 8,000 tokens |
| Inputs and features | |||
| Text | Yes | Yes | Yes |
| Images | No | No | No |
| PDFs | No | No | No |
| Audio | No | No | No |
| Video | No | No | No |
| Reasoning | Yes | No | No |
| Tool calling | Yes | Yes | Yes |
| Structured output | Yes | No | No |
| Availability | |||
| Weights | Proprietary | OpenApache 2.0 | OpenApache-2.0 |
| API model ID | qwen-flash | — | — |
| API providers | 6 | 14 (best) | 1 |
| Released | Jul 28, 2025 | Jul 28, 2025 | Jun 30, 2025 |
| Knowledge cutoff | Apr 2024 | — | — |
What would a month cost?
Enter your expected volume in millions of tokens. List prices only; caching and batch discounts would lower these.
Qwen Flash$1.30
Qwen3 30B-A3B Instruct 2507$1.60
ERNIE 4.5 21B A3B$1.26
Which should you choose?
Which is better: Qwen Flash, Qwen3 30B-A3B Instruct 2507 or ERNIE 4.5 21B A3B?
Qwen Flash is the better all-round choice, scoring 69/100 against Qwen3 30B-A3B Instruct 2507 (57) and ERNIE 4.5 21B A3B (57). It leads on inputs & features and context window. ERNIE 4.5 21B A3B wins on price. 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, Qwen Flash, Qwen3 30B-A3B Instruct 2507 or ERNIE 4.5 21B A3B?
ERNIE 4.5 21B A3B is cheaper at $0.07 input / $0.28 output per million tokens (median across 1 API provider). Qwen Flash costs $0.05 input / $0.40 output per million tokens (official Alibaba API price); Qwen3 30B-A3B Instruct 2507 costs $0.10 input / $0.30 output per million tokens (median across 12 API providers). At a typical mix of three input tokens to one output token, that is $0.122 per million tokens for ERNIE 4.5 21B A3B versus $0.138 for Qwen Flash (1.1× as much) and $0.15 for Qwen3 30B-A3B Instruct 2507 (1.2× as much).
Which scores higher on benchmarks?
There is no independent benchmark that covers all three models yet. Qwen Flash has not been scored yet, Qwen3 30B-A3B Instruct 2507 has an ECI of 137.3 and ERNIE 4.5 21B A3B has not been scored yet.
Which is better for coding?
There are no published SWE-bench Verified results for Qwen Flash, Qwen3 30B-A3B Instruct 2507 and ERNIE 4.5 21B A3B yet, so there is no like-for-like coding score. Test both on a sample of your own tasks. All three support tool calling for agent workflows.
Which has the bigger context window?
Qwen Flash has the largest context window at 1,000,000 tokens, against 262,144 for Qwen3 30B-A3B Instruct 2507 and 131,072 for ERNIE 4.5 21B A3B. Maximum output per response: Qwen Flash up to 32,768, Qwen3 30B-A3B Instruct 2507 up to 16,384, ERNIE 4.5 21B A3B up to 8,000 tokens.
Which can read images, PDFs, audio or video?
Qwen Flash accepts text; Qwen3 30B-A3B Instruct 2507 accepts text; ERNIE 4.5 21B A3B accepts text. They handle the same number of input types.
Are any of these open source?
Qwen3 30B-A3B Instruct 2507 and ERNIE 4.5 21B A3B publishes its weights (Apache 2.0 and Apache-2.0) and can be self-hosted; Qwen Flash is proprietary.
Which is newer?
Qwen Flash is the newest, released Jul 28, 2025. Qwen3 30B-A3B Instruct 2507 came out Jul 28, 2025; ERNIE 4.5 21B A3B came out Jun 30, 2025. Knowledge cutoff: Qwen Flash Apr 2024.
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.