| Signal | Llama 3.3 Nemotron Super 49B V1.5 | Delta | Qwen3 8B |
|---|---|---|---|
Capabilities | 67 | -- | |
Benchmarks | 59 | 0 | |
Pricing | 0 | -- | |
Context window size | 81 | +8 | |
Recency | 100 | +29 | |
Output Capacity | 20 | -45 | |
| Overall Result | 2 wins | of 6 | 2 wins |
6
days higher
7
days
17
days higher
NVIDIA
Alibaba
Qwen3 8B saves you $5.00/month
That's $60.00/year compared to Llama 3.3 Nemotron Super 49B V1.5 at your current usage level of 100K calls/month.
| Metric | Llama 3.3 Nemotron Super 49B V1.5 | Qwen3 8B | Winner |
|---|---|---|---|
| Overall Score | 61 | 61 | -- |
| Rank | #97 | #98 | Llama 3.3 Nemotron Super 49B V1.5 |
| Quality Rank | #97 | #98 | Llama 3.3 Nemotron Super 49B V1.5 |
| Adoption Rank | #97 | #98 | Llama 3.3 Nemotron Super 49B V1.5 |
| Parameters | 49B | 8B | -- |
| Context Window | 131K | 41K | Llama 3.3 Nemotron Super 49B V1.5 |
| Pricing | $0.10/$0.40/M | $0.05/$0.40/M | -- |
| Signal Scores | |||
| Capabilities | 67 | 67 | Llama 3.3 Nemotron Super 49B V1.5 |
| Benchmarks | 59 | 60 | Qwen3 8B |
| Pricing | 0 | 0 | Llama 3.3 Nemotron Super 49B V1.5 |
| Context window size | 81 | 73 | Llama 3.3 Nemotron Super 49B V1.5 |
| Recency | 100 | 71 | Llama 3.3 Nemotron Super 49B V1.5 |
| Output Capacity | 20 | 65 | Qwen3 8B |
Our score (0-100) is driven by benchmark performance (90%) from Arena Elo ratings, MMLU, GPQA, HumanEval, SWE-bench, and 15+ standardized evaluations. Capabilities and context window serve as tiebreakers (10%). Here's what the scores mean for these two models:
Scores 61/100 (rank #97), placing it in the top 67% of all 290 models tracked.
Scores 61/100 (rank #98), placing it in the top 67% of all 290 models tracked.
With only a 0-point gap, these models are in the same performance tier. The practical difference in output quality is minimal - your choice should depend on pricing, latency requirements, and specific feature needs.
Qwen3 8B offers 10% better value per quality point. At 1M tokens/day, you'd spend $6.75/month with Qwen3 8B vs $7.50/month with Llama 3.3 Nemotron Super 49B V1.5 - a $0.75 monthly difference.
Both models have comparable response speeds. For most applications, the latency difference is negligible.
When latency matters most: Interactive chatbots, IDE code completion, real-time translation, and user-facing applications where response time directly impacts experience. For batch processing, background summarization, or offline analysis, latency is less critical.
Code generation & review
Higher benchmark score (0/100) indicates stronger performance on coding tasks like generating functions, debugging, and refactoring
Customer support chatbot
Faster response time (speed score 0/100) is critical for user-facing chat. Llama 3.3 Nemotron Super 49B V1.5 also offers lower per-token costs for high-volume support
Long document analysis
Larger context window (131K tokens) can process longer documents, contracts, and research papers in a single pass
Batch data extraction
Lower output pricing ($0.40/M) reduces costs when processing thousands of records daily
Creative writing & content
Higher overall composite score (61/100) correlates with better nuance, coherence, and style in long-form content
Llama 3.3 Nemotron Super 49B V1.5 and Qwen3 8B are extremely close in overall performance (only 0 points apart). Your best choice depends entirely on which specific strengths matter most for your use case.
Best for Quality
Llama 3.3 Nemotron Super 49B V1.5
Marginally better benchmark scores; both are excellent
Best for Cost
Qwen3 8B
10% lower pricing; better value at scale
Best for Reliability
Llama 3.3 Nemotron Super 49B V1.5
Higher uptime and faster response speeds
Best for Prototyping
Llama 3.3 Nemotron Super 49B V1.5
Stronger community support and better developer experience
Best for Production
Llama 3.3 Nemotron Super 49B V1.5
Wider enterprise adoption and proven at scale
by NVIDIA
| Capability | Llama 3.3 Nemotron Super 49B V1.5 | Qwen3 8B |
|---|---|---|
| Vision (Image Input) | ||
| Function Calling | ||
| Streaming | ||
| JSON Mode | ||
| Reasoning | ||
| Web Search | ||
| Image Output |
NVIDIA
Alibaba
Qwen3 8B saves you $0.0900/month
That's 14% cheaper than Llama 3.3 Nemotron Super 49B V1.5 at 1,000 tokens/request and 100 requests/day.
Assumes 60% input / 40% output token ratio per request. Actual costs may vary based on your usage pattern.
| Parameter | Llama 3.3 Nemotron Super 49B V1.5 | Qwen3 8B |
|---|---|---|
| Context Window | 131K | 41K |
| Max Output Tokens | -- | 8,192 |
| Open Source | Yes | Yes |
| Created | Oct 10, 2025 | Apr 28, 2025 |
Both Llama 3.3 Nemotron Super 49B V1.5 and Qwen3 8B score 61/100, making them extremely close competitors. Choose based on pricing, provider ecosystem, or specific capability requirements.
Llama 3.3 Nemotron Super 49B V1.5 is ranked #97 and Qwen3 8B is ranked #98 out of 290+ AI models. Rankings use a composite score combining benchmark performance (90%) from MMLU, GPQA, HumanEval, SWE-bench, and 15+ standardized evaluations, with capabilities and context window as tiebreakers (10%). Scores update hourly.
Llama 3.3 Nemotron Super 49B V1.5 is cheaper at $0.40/M output tokens vs Qwen3 8B's $0.40/M output tokens - 1.0x more expensive. Input token pricing: Llama 3.3 Nemotron Super 49B V1.5 at $0.10/M vs Qwen3 8B at $0.05/M.
Llama 3.3 Nemotron Super 49B V1.5 has a larger context window of 131,072 tokens compared to Qwen3 8B's 40,960 tokens. A larger context window means the model can process longer documents and conversations.