ERNIE 4.5 21B A3B vs Nemotron Nano 9B v2 vs Qwen Flash
Qwen Flash comes out ahead, 69 to 62 and 57 on our weighted score, though Nemotron Nano 9B v2 is 25% cheaper per token.
BaiduERNIE 4.5 21B A3B
57/100- ECI—
- Price$0.07 / $0.28
- Context131K
NVIDIANemotron Nano 9B v2
62/100- ECI—
- Price$0.06 / $0.23
- Context131K
- Our pick
Alibaba (Qwen)Qwen Flash
69/100- ECI—
- Price$0.05 / $0.40
- Context1M
Qwen Flash is our pick
Qwen Flash is the better all-round choice, scoring 69/100 against Nemotron Nano 9B v2 (62) and ERNIE 4.5 21B A3B (57). It leads on inputs & features and context window. Nemotron Nano 9B v2 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 priceNemotron Nano 9B v2Nemotron Nano 9B v2 $0.102 · ERNIE 4.5 21B A3B $0.122 · Qwen Flash $0.138 per 1M tokens (3:1 blend)
- Longest contextQwen FlashQwen Flash 1,000,000 · ERNIE 4.5 21B A3B 131,072 · Nemotron Nano 9B v2 131,072 tokens
- Widest inputsSame inputsERNIE 4.5 21B A3B: Text · Nemotron Nano 9B v2: Text · Qwen Flash: Text
- Self-hostingERNIE 4.5 21B A3B and Nemotron Nano 9B v2Publishes downloadable weights (Apache-2.0)
| Measure | Weight | ERNIE 4.5 21B A3B | Nemotron Nano 9B v2 | Qwen Flash |
|---|---|---|---|---|
| Price | 50% | 89 | 93 | 87 |
| Inputs & features | 30% | 25 | 35 | 45 |
| Context window | 20% | 25 | 25 | 60 |
| Overall | 100% | 57/100 | 62/100 | 69/100 |
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 | ERNIE 4.5 21B A3BBaidu | Nemotron Nano 9B v2NVIDIA | Qwen FlashAlibaba (Qwen) |
|---|---|---|---|
| Capability | |||
| Capabilities Index (ECI) | — | — | — |
| ECI rank | — | — | — |
| Price per million tokens | |||
| Input | $0.07 | $0.06 | $0.05 (best) |
| Output | $0.28 | $0.23 (best) | $0.40 |
| Cached input | — | — | $0.01 |
| Blended (3:1) | $0.122 | $0.102 (best) | $0.138 |
| Long-context rate | Same rate | Same rate | Over 256K: $0.25 / $2.00 |
| Price source | Median of 1 providers | Median of 3 providers | Official Alibaba API |
| Limits | |||
| Context window | 131,072 tokens | 131,072 tokens | 1,000,000 tokens (best) |
| Max output | 8,000 tokens | 131,072 tokens (best) | 32,768 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 | No | Yes | Yes |
| Tool calling | Yes | Yes | Yes |
| Structured output | No | No | Yes |
| Availability | |||
| Weights | OpenApache-2.0 | Open | Proprietary |
| API model ID | — | — | qwen-flash |
| API providers | 1 | 3 | 6 (best) |
| Released | Jun 30, 2025 | Aug 18, 2025 | Jul 28, 2025 |
| Knowledge cutoff | — | Sep 2024 | 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.
- ERNIE 4.5 21B A3B$1.26
- Nemotron Nano 9B v2$1.06
- Qwen Flash$1.30
Which should you choose?
Which is better: ERNIE 4.5 21B A3B, Nemotron Nano 9B v2 or Qwen Flash?
Qwen Flash is the better all-round choice, scoring 69/100 against Nemotron Nano 9B v2 (62) and ERNIE 4.5 21B A3B (57). It leads on inputs & features and context window. Nemotron Nano 9B v2 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, ERNIE 4.5 21B A3B, Nemotron Nano 9B v2 or Qwen Flash?
Nemotron Nano 9B v2 is cheaper at $0.06 input / $0.23 output per million tokens (median across 3 API providers). ERNIE 4.5 21B A3B costs $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). At a typical mix of three input tokens to one output token, that is $0.102 per million tokens for Nemotron Nano 9B v2 versus $0.122 for ERNIE 4.5 21B A3B (1.2× as much) and $0.138 for Qwen Flash (1.3× as much).
Which scores higher on benchmarks?
There is no independent benchmark that covers all three models yet. ERNIE 4.5 21B A3B has not been scored yet, Nemotron Nano 9B v2 has not been scored yet and Qwen Flash has not been scored yet.
Which is better for coding?
There are no published SWE-bench Verified results for ERNIE 4.5 21B A3B, Nemotron Nano 9B v2 and Qwen Flash 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 131,072 for ERNIE 4.5 21B A3B and 131,072 for Nemotron Nano 9B v2. Maximum output per response: ERNIE 4.5 21B A3B up to 8,000, Nemotron Nano 9B v2 up to 131,072, Qwen Flash up to 32,768 tokens.
Which can read images, PDFs, audio or video?
ERNIE 4.5 21B A3B accepts text; Nemotron Nano 9B v2 accepts text; Qwen Flash accepts text. They handle the same number of input types.
Are any of these open source?
ERNIE 4.5 21B A3B and Nemotron Nano 9B v2 publishes its weights (Apache-2.0) and can be self-hosted; Qwen Flash is proprietary.
Which is newer?
Nemotron Nano 9B v2 is the newest, released Aug 18, 2025. Qwen Flash came out Jul 28, 2025; ERNIE 4.5 21B A3B came out Jun 30, 2025. Knowledge cutoff: Nemotron Nano 9B v2 Sep 2024, 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.
