Model Comparison
Llama 3 Instruct 8B
vs. Qwen3.5 0.8B (Reasoning)
Comparing 2 AI models · 11 benchmarks · Meta, Alibaba
Recommended Pick
Me Llama 3 Instruct 8B 8 metric wins Strongest on: Throughput, TTFT, Latency
Best Value
Qwen3.5 0.8B (Reasoning)
100.0 value score
5.8 reasoning / $0.02/1M
Lowest Price
Qwen3.5 0.8B (Reasoning)
$0.01/1M input price
Best Reasoning
Llama 3 Instruct 8B
17.2 reasoning score
Blends available reasoning benchmarks
Best for Coding
Qwen3.5 0.8B (Reasoning)
15.0 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
Qwen3.5 0.8B (Reasoning) has the strongest quality-to-price mix at 100.0 out of 100 value points.
Price gap
Qwen3.5 0.8B (Reasoning) is 4.5x cheaper on input tokens than Llama 3 Instruct 8B.
Speed gap
Llama 3 Instruct 8B generates about 1.7x as many tokens per second as Qwen3.5 0.8B (Reasoning).
Reasoning gap
Llama 3 Instruct 8B leads Qwen3.5 0.8B (Reasoning) by 11.4 points on reasoning.
Top-pick rationale
Llama 3 Instruct 8B wins 8 measurable categories, including Throughput, TTFT, Latency, Reasoning.
Response Face-Off
Run one prompt through the selected models and compare response quality with live speed and cost context.
Llama 3 Instruct 8B
Meta
TTFT
—
Time
—
tok/s
—
Tokens
—
Cost
—
Qwen3.5 0.8B (Reasoning)
Alibaba
TTFT
—
Time
—
tok/s
—
Tokens
—
Cost
—
Which answer was more useful?
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Full Comparison
| Metric | Top Pick Me Llama 3 Instruct 8B | Al Qwen3.5 0.8B (Reasoning) |
|---|---|---|
| Pricing per 1M tokens | ||
| Input Cost | $0.04/1M | $0.01/1M |
| Output Cost | $0.14/1M | $0.05/1M |
| Blended (3:1) | $0.07/1M | $0.02/1M |
| Specifications | ||
| Organization | Meta | Alibaba |
| Release Date | Apr 18, 2024 | Mar 2, 2026 |
| Performance & Speed | ||
| Throughput | 84.3 tok/s | 48.5 tok/s |
| TTFT | 474ms | 525ms |
| Latency | 474ms | 41727ms |
| Composite Indices | ||
| Value Score | 85.1 | 100.0 |
| Reasoning Score | 17.2 | 5.8 |
| Intelligence | 1.2 | 5.0 |
| Coding | — | 15.0 |
| Standard Benchmarks | ||
| GPQA | 29.6% | 11.1% |
| MMLU Pro | 40.5% | — |
| HLE | 5.1% | 1.2% |
| LiveCodeBench | 9.6% | — |
| MATH 500 | 49.9% | — |
| AIME (Original) | 0.0% | — |
| SciCode | 11.9% | 0.0% |
| LCR | 0.0% | 5.3% |
| IFBench | 24.6% | 21.5% |
| TAU-bench v2 | 0.0% | 47.7% |
| TerminalBench Hard | 0.0% | 0.0% |
Key Takeaways
Qwen3.5 0.8B (Reasoning) offers the best value at $0.01/1M, making it ideal for high-volume applications and cost-conscious projects.
Llama 3 Instruct 8B has the strongest reasoning profile with a 17.2 reasoning score, combining the available reasoning-heavy benchmarks.
Qwen3.5 0.8B (Reasoning) reaches a 15.0 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 Instruct 8B
- Complex reasoning tasks
- Research & analysis
Qwen3.5 0.8B (Reasoning)
- Cost-sensitive applications
- High-volume processing
- Code generation
- Software development
