Model Comparison
Llama 3 Instruct 70B
vs. Qwen3.5 0.8B (Non-reasoning)
Comparing 2 AI models · 11 benchmarks · Meta, Alibaba
Recommended Pick
Al Qwen3.5 0.8B (Non-reasoning) 11 metric wins Strongest on: Value, Input price, Output price
Best Value
Qwen3.5 0.8B (Non-reasoning)
100.0 value score
12.8 reasoning / $0.02/1M
Lowest Price
Qwen3.5 0.8B (Non-reasoning)
$0.01/1M input price
Best Reasoning
Llama 3 Instruct 70B
19.9 reasoning score
Blends available reasoning benchmarks
Best for Coding
Llama 3 Instruct 70B
6.8 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 (Non-reasoning) has the strongest quality-to-price mix at 100.0 out of 100 value points.
Price gap
Qwen3.5 0.8B (Non-reasoning) is 65x cheaper on input tokens than Llama 3 Instruct 70B.
Speed gap
Qwen3.5 0.8B (Non-reasoning) generates about 2.3x as many tokens per second as Llama 3 Instruct 70B.
Reasoning gap
Llama 3 Instruct 70B leads Qwen3.5 0.8B (Non-reasoning) by 7.1 points on reasoning.
Coding gap
Llama 3 Instruct 70B leads Qwen3.5 0.8B (Non-reasoning) by 5.8 points on coding.
Response Face-Off
Run one prompt through the selected models and compare response quality with live speed and cost context.
Llama 3 Instruct 70B
Meta
TTFT
—
Time
—
tok/s
—
Tokens
—
Cost
—
Qwen3.5 0.8B (Non-reasoning)
Alibaba
TTFT
—
Time
—
tok/s
—
Tokens
—
Cost
—
Which answer was more useful?
Full Comparison
| Metric | Me Llama 3 Instruct 70B | Top Pick Al Qwen3.5 0.8B (Non-reasoning) |
|---|---|---|
| Pricing per 1M tokens | ||
| Input Cost | $0.65/1M | $0.01/1M |
| Output Cost | $2.75/1M | $0.05/1M |
| Blended (3:1) | $1.18/1M | $0.02/1M |
| Specifications | ||
| Organization | Meta | Alibaba |
| Release Date | Apr 18, 2024 | Mar 2, 2026 |
| Performance & Speed | ||
| Throughput | 43.7 tok/s | 98.8 tok/s |
| TTFT | 756ms | 249ms |
| Latency | 756ms | 249ms |
| Composite Indices | ||
| Value Score | 2.6 | 100.0 |
| Reasoning Score | 19.9 | 12.8 |
| Intelligence | 8.9 | 9.9 |
| Coding | 6.8 | 1.0 |
| Standard Benchmarks | ||
| GPQA | 37.9% | 23.6% |
| MMLU Pro | 57.4% | — |
| HLE | 4.4% | 4.9% |
| LiveCodeBench | 19.8% | — |
| MATH 500 | 48.3% | — |
| AIME (Original) | 0.0% | — |
| SciCode | 18.9% | 2.9% |
| LCR | 0.0% | 6.7% |
| IFBench | 37.1% | 21.6% |
| TAU-bench v2 | 0.0% | 65.2% |
| TerminalBench Hard | 0.8% | 0.0% |
Key Takeaways
Qwen3.5 0.8B (Non-reasoning) offers the best value at $0.01/1M, making it ideal for high-volume applications and cost-conscious projects.
Llama 3 Instruct 70B has the strongest reasoning profile with a 19.9 reasoning score, combining the available reasoning-heavy benchmarks.
Llama 3 Instruct 70B reaches a 6.8 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 70B
- Complex reasoning tasks
- Research & analysis
- Code generation
- Software development
Qwen3.5 0.8B (Non-reasoning)
- Cost-sensitive applications
- High-volume processing
