Model Comparison
Llama 3.1 Nemotron Nano 4B v1.1 (Reasoning)
vs. Qwen3 VL 8B Instruct
Comparing 2 AI models · 12 benchmarks · NVIDIA, Alibaba
Recommended Pick
NV Llama 3.1 Nemotron Nano 4B v1.1 (Reasoning) 10 metric wins Strongest on: Input price, Output price, TTFT
Lowest Price
Llama 3.1 Nemotron Nano 4B v1.1 (Reasoning)
$0.00/1M input price
Best Reasoning
Llama 3.1 Nemotron Nano 4B v1.1 (Reasoning)
46.5 reasoning score
Blends available reasoning benchmarks
Best for Coding
Qwen3 VL 8B Instruct
7.3 coding index
Composite Indices
Higher is better; speed and price are normalized
Standard Benchmarks
Only benchmarks with data are shown
Differences That Matter
Price gap
Llama 3.1 Nemotron Nano 4B v1.1 (Reasoning) is ∞x cheaper on input tokens than Qwen3 VL 8B Instruct.
Reasoning gap
Llama 3.1 Nemotron Nano 4B v1.1 (Reasoning) leads Qwen3 VL 8B Instruct by 23.6 points on reasoning.
Top-pick rationale
Llama 3.1 Nemotron Nano 4B v1.1 (Reasoning) wins 10 measurable categories, including Input price, Output price, TTFT, Latency.
Response Face-Off
Run one prompt through the selected models and compare response quality with live speed and cost context.
Llama 3.1 Nemotron Nano 4B v1.1 (Reasoning)
NVIDIA
TTFT
—
Time
—
tok/s
—
Tokens
—
Cost
—
Qwen3 VL 8B Instruct
Alibaba
TTFT
—
Time
—
tok/s
—
Tokens
—
Cost
—
Which answer was more useful?
Full Comparison
| Metric | Top Pick NV Llama 3.1 Nemotron Nano 4B v1.1 (Reasoning) | Al Qwen3 VL 8B Instruct |
|---|---|---|
| Pricing per 1M tokens | ||
| Input Cost | $0.00/1M | $0.18/1M |
| Output Cost | $0.00/1M | $0.70/1M |
| Blended (3:1) | — | $0.31/1M |
| Specifications | ||
| Organization | NVIDIA | Alibaba |
| Release Date | May 20, 2025 | Oct 14, 2025 |
| Performance & Speed | ||
| Throughput | — | 147.7 tok/s |
| TTFT | — | 928ms |
| Latency | — | 928ms |
| Composite Indices | ||
| Value Score | — | 100.0 |
| Reasoning Score | 46.5 | 22.9 |
| Intelligence | 14.4 | 14.3 |
| Coding | — | 7.3 |
| Math | 50.0 | 27.3 |
| Standard Benchmarks | ||
| GPQA | 40.8% | 42.7% |
| MMLU Pro | 55.6% | 68.6% |
| HLE | 5.1% | 2.9% |
| LiveCodeBench | 49.3% | 33.2% |
| MATH 500 | 94.7% | — |
| AIME 2025 | 50.0% | 27.3% |
| AIME (Original) | 70.7% | — |
| SciCode | 10.1% | 17.4% |
| LCR | 0.0% | 15.3% |
| IFBench | 25.5% | 32.3% |
| TAU-bench v2 | 11.7% | 29.2% |
| TerminalBench Hard | — | 2.3% |
Key Takeaways
Llama 3.1 Nemotron Nano 4B v1.1 (Reasoning) offers the best value at $0.00/1M, making it ideal for high-volume applications and cost-conscious projects.
Llama 3.1 Nemotron Nano 4B v1.1 (Reasoning) has the strongest reasoning profile with a 46.5 reasoning score, combining the available reasoning-heavy benchmarks.
Qwen3 VL 8B Instruct reaches a 7.3 coding index, making it the top choice for software development and code generation tasks.
All models support context windows of ∞+ tokens, suitable for processing lengthy documents and maintaining extended conversations.
When to Choose Each Model
Llama 3.1 Nemotron Nano 4B v1.1 (Reasoning)
- Cost-sensitive applications
- High-volume processing
- Complex reasoning tasks
- Research & analysis
Qwen3 VL 8B Instruct
- Code generation
- Software development
