ERNIE 4.5 300B A47B vs Llama 3.3 Nemotron Super 49B v1.5
Llama 3.3 Nemotron Super 49B v1.5 comes out ahead, 48 to 43 on our weighted score, and it is the cheaper option too.
BaiduERNIE 4.5 300B A47B
43/100- ECI—
- Price$0.28 / $1.10
- Context131K
- Our pick
NVIDIALlama 3.3 Nemotron Super 49B v1.5
48/100- ECI—
- Price$0.40 / $0.40
- Context131K
Add a model
Make it a three-way comparison.
Llama 3.3 Nemotron Super 49B v1.5 is our pick
Llama 3.3 Nemotron Super 49B v1.5 is the better all-round choice, scoring 48/100 against ERNIE 4.5 300B A47B (43). It leads on price and 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 priceLlama 3.3 Nemotron Super 49B v1.5Llama 3.3 Nemotron Super 49B v1.5 $0.40 · ERNIE 4.5 300B A47B $0.485 per 1M tokens (3:1 blend)
- Longest contextAbout the sameERNIE 4.5 300B A47B 131,072 · Llama 3.3 Nemotron Super 49B v1.5 131,072 tokens
- Widest inputsSame inputsERNIE 4.5 300B A47B: Text · Llama 3.3 Nemotron Super 49B v1.5: Text
- Self-hostingAll open weightsEvery model here can be downloaded and run on your own hardware
| Measure | Weight | ERNIE 4.5 300B A47B | Llama 3.3 Nemotron Super 49B v1.5 |
|---|---|---|---|
| Price | 50% | 62 | 66 |
| Inputs & features | 30% | 25 | 35 |
| Context window | 20% | 25 | 25 |
| Overall | 100% | 43/100 | 48/100 |
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 300B A47BBaidu | Llama 3.3 Nemotron Super 49B v1.5NVIDIA |
|---|---|---|
| Capability | ||
| Capabilities Index (ECI) | — | — |
| ECI rank | — | — |
| Price per million tokens | ||
| Input | $0.28 (best) | $0.40 |
| Output | $1.10 | $0.40 (best) |
| Cached input | — | — |
| Blended (3:1) | $0.485 | $0.40 (best) |
| Long-context rate | Same rate | Same rate |
| Price source | Median of 1 providers | Median of 1 providers |
| Limits | ||
| Context window | 131,072 tokens | 131,072 tokens |
| Max output | 12,000 tokens | 131,072 tokens (best) |
| Inputs and features | ||
| Text | Yes | Yes |
| Images | No | No |
| PDFs | No | No |
| Audio | No | No |
| Video | No | No |
| Reasoning | No | Yes |
| Tool calling | Yes | Yes |
| Structured output | No | No |
| Availability | ||
| Weights | OpenApache-2.0 | Open |
| API model ID | — | — |
| API providers | 1 | 1 |
| Released | Jun 30, 2025 | Jul 25, 2025 |
| Knowledge cutoff | — | — |
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 300B A47B$5.00
- Llama 3.3 Nemotron Super 49B v1.5$4.80
Which should you choose?
Which is better: ERNIE 4.5 300B A47B or Llama 3.3 Nemotron Super 49B v1.5?
Llama 3.3 Nemotron Super 49B v1.5 is the better all-round choice, scoring 48/100 against ERNIE 4.5 300B A47B (43). It leads on price and 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 300B A47B or Llama 3.3 Nemotron Super 49B v1.5?
Llama 3.3 Nemotron Super 49B v1.5 is cheaper at $0.40 input / $0.40 output per million tokens (median across 1 API provider). ERNIE 4.5 300B A47B costs $0.28 input / $1.10 output per million tokens (median across 1 API provider). At a typical mix of three input tokens to one output token, that is $0.40 per million tokens for Llama 3.3 Nemotron Super 49B v1.5 versus $0.485 for ERNIE 4.5 300B A47B (1.2× as much).
Which scores higher on benchmarks?
There is no independent benchmark that covers both models yet. ERNIE 4.5 300B A47B has not been scored yet and Llama 3.3 Nemotron Super 49B v1.5 has not been scored yet.
Which is better for coding?
There are no published SWE-bench Verified results for ERNIE 4.5 300B A47B and Llama 3.3 Nemotron Super 49B v1.5 yet, so there is no like-for-like coding score. Test both on a sample of your own tasks. Both support tool calling for agent workflows.
Which has the bigger context window?
ERNIE 4.5 300B A47B and Llama 3.3 Nemotron Super 49B v1.5 share the same 131,072-token context window. Maximum output per response: ERNIE 4.5 300B A47B up to 12,000, Llama 3.3 Nemotron Super 49B v1.5 up to 131,072 tokens.
Which can read images, PDFs, audio or video?
ERNIE 4.5 300B A47B accepts text; Llama 3.3 Nemotron Super 49B v1.5 accepts text. They handle the same number of input types.
Are any of these open source?
Yes, both publish their weights (Apache-2.0), so you can self-host them.
Which is newer?
Llama 3.3 Nemotron Super 49B v1.5 is the newest, released Jul 25, 2025. ERNIE 4.5 300B A47B came out Jun 30, 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.
Related comparisons
- Add Codestral 25.08Three-way comparison
- ERNIE 4.5 300B A47B vs Codestral 25.08Mistral AI
- ERNIE 4.5 300B A47B vs GLM-4.5-AirZ.ai (Zhipu)
- ERNIE 4.5 300B A47B vs Grok Code Fast 1xAI
- Llama 3.3 Nemotron Super 49B v1.5 vs GLM-4.5-AirZ.ai (Zhipu)
- Llama 3.3 Nemotron Super 49B v1.5 vs Codestral 25.08Mistral AI
- Llama 3.3 Nemotron Super 49B v1.5 vs Gemma-SEA-LION-v4-27B-ITAI Singapore
