Model Comparison
V4 Flash (Reasoning, Max Effort)
vs. Llama Nemotron Super 49B v1.5 (Reasoning)
Comparing 2 AI models · 12 benchmarks · DeepSeek, NVIDIA
Recommended Pick
De V4 Flash (Reasoning, Max Effort) 11 metric wins Strongest on: Output price, Throughput, Intelligence
Best Value
Llama Nemotron Super 49B v1.5 (Reasoning)
100.0 value score
62.6 reasoning / $0.18/1M
Lowest Price
Llama Nemotron Super 49B v1.5 (Reasoning)
$0.10/1M input price
Best Reasoning
Llama Nemotron Super 49B v1.5 (Reasoning)
62.6 reasoning score
Blends available reasoning benchmarks
Best for Coding
V4 Flash (Reasoning, Max Effort)
38.7 coding index
Composite Indices
Higher is better; speed and price are normalized
Standard Benchmarks
Only benchmarks with data are shown
Differences That Matter
Best value
Llama Nemotron Super 49B v1.5 (Reasoning) has the strongest quality-to-price mix at 100.0 out of 100 value points.
Price gap
Llama Nemotron Super 49B v1.5 (Reasoning) is 1.4x cheaper on input tokens than V4 Flash (Reasoning, Max Effort).
Speed gap
V4 Flash (Reasoning, Max Effort) generates about 2.3x as many tokens per second as Llama Nemotron Super 49B v1.5 (Reasoning).
Reasoning gap
Llama Nemotron Super 49B v1.5 (Reasoning) leads V4 Flash (Reasoning, Max Effort) by 6.6 points on reasoning.
Coding gap
V4 Flash (Reasoning, Max Effort) leads Llama Nemotron Super 49B v1.5 (Reasoning) by 23.6 points on coding.
Response Face-Off
Run one prompt through the selected models and compare response quality with live speed and cost context.
V4 Flash (Reasoning, Max Effort)
DeepSeek
TTFT
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Time
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tok/s
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Tokens
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Cost
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Llama Nemotron Super 49B v1.5 (Reasoning)
NVIDIA
TTFT
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Time
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tok/s
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Tokens
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Cost
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Which answer was more useful?
Full Comparison
| Metric | Top Pick De V4 Flash (Reasoning, Max Effort) | NV Llama Nemotron Super 49B v1.5 (Reasoning) |
|---|---|---|
| Pricing per 1M tokens | ||
| Input Cost | $0.14/1M | $0.10/1M |
| Output Cost | $0.28/1M | $0.40/1M |
| Blended (3:1) | $0.18/1M | $0.18/1M |
| Specifications | ||
| Organization | DeepSeek | NVIDIA |
| Release Date | Apr 24, 2026 | Jul 25, 2025 |
| Performance & Speed | ||
| Throughput | 107.8 tok/s | 46.9 tok/s |
| TTFT | 911ms | 328ms |
| Latency | 52997ms | 42969ms |
| Composite Indices | ||
| Value Score | 89.5 | 100.0 |
| Reasoning Score | 56.0 | 62.6 |
| Intelligence | 46.5 | 18.7 |
| Coding | 38.7 | 15.1 |
| Math | — | 76.7 |
| Standard Benchmarks | ||
| GPQA | 89.4% | 74.8% |
| MMLU Pro | — | 81.4% |
| HLE | 32.1% | 6.8% |
| LiveCodeBench | — | 73.7% |
| MATH 500 | — | 98.3% |
| AIME 2025 | — | 76.7% |
| AIME (Original) | — | 86.0% |
| SciCode | 44.9% | 34.8% |
| LCR | 63.0% | 34.0% |
| IFBench | 79.2% | 37.0% |
| TAU-bench v2 | 95.0% | 28.1% |
| TerminalBench Hard | 35.6% | 5.3% |
Key Takeaways
Llama Nemotron Super 49B v1.5 (Reasoning) offers the best value at $0.10/1M, making it ideal for high-volume applications and cost-conscious projects.
Llama Nemotron Super 49B v1.5 (Reasoning) has the strongest reasoning profile with a 62.6 reasoning score, combining the available reasoning-heavy benchmarks.
V4 Flash (Reasoning, Max Effort) reaches a 38.7 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
V4 Flash (Reasoning, Max Effort)
- Code generation
- Software development
Llama Nemotron Super 49B v1.5 (Reasoning)
- Cost-sensitive applications
- High-volume processing
- Complex reasoning tasks
- Research & analysis
