Model Comparison
7B Instruct
vs. Qwen3.5 0.8B (Non-reasoning)
Comparing 2 AI models · 11 benchmarks · Mistral, Alibaba
Recommended Pick
Al Qwen3.5 0.8B (Non-reasoning) 14 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
Qwen3.5 0.8B (Non-reasoning)
12.8 reasoning score
Blends available reasoning benchmarks
Best for Coding
Qwen3.5 0.8B (Non-reasoning)
1.0 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 (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 20x cheaper on input tokens than 7B Instruct.
Speed gap
7B Instruct generates about 1.6x as many tokens per second as Qwen3.5 0.8B (Non-reasoning).
Reasoning gap
Qwen3.5 0.8B (Non-reasoning) leads 7B Instruct by 4.5 points on reasoning.
Top-pick rationale
Qwen3.5 0.8B (Non-reasoning) wins 14 measurable categories, including Value, Input price, Output price, Blended price.
Response Face-Off
Run one prompt through the selected models and compare response quality with live speed and cost context.
7B Instruct
Mistral
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 | Mi 7B Instruct | Top Pick Al Qwen3.5 0.8B (Non-reasoning) |
|---|---|---|
| Pricing per 1M tokens | ||
| Input Cost | $0.20/1M | $0.01/1M |
| Output Cost | $0.23/1M | $0.05/1M |
| Blended (3:1) | $0.21/1M | $0.02/1M |
| Specifications | ||
| Organization | Mistral | Alibaba |
| Release Date | Sep 27, 2023 | Mar 2, 2026 |
| Performance & Speed | ||
| Throughput | 92.0 tok/s | 56.1 tok/s |
| TTFT | 369ms | 299ms |
| Latency | 369ms | 299ms |
| Composite Indices | ||
| Value Score | 6.3 | 100.0 |
| Reasoning Score | 8.3 | 12.8 |
| Intelligence | 7.4 | 9.9 |
| Coding | — | 1.0 |
| Standard Benchmarks | ||
| GPQA | 17.7% | 23.6% |
| MMLU Pro | 24.5% | — |
| HLE | 4.3% | 4.9% |
| LiveCodeBench | 4.6% | — |
| MATH 500 | 12.1% | — |
| AIME (Original) | 0.0% | — |
| SciCode | 2.4% | 2.9% |
| LCR | 0.0% | 6.7% |
| IFBench | 19.9% | 21.6% |
| TAU-bench v2 | 0.0% | 65.2% |
| TerminalBench Hard | — | 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.
Qwen3.5 0.8B (Non-reasoning) has the strongest reasoning profile with a 12.8 reasoning score, combining the available reasoning-heavy benchmarks.
Qwen3.5 0.8B (Non-reasoning) reaches a 1.0 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
7B Instruct
- General-purpose AI
- Versatile applications
Qwen3.5 0.8B (Non-reasoning)
- Cost-sensitive applications
- High-volume processing
- Complex reasoning tasks
- Research & analysis
- Code generation
- Software development
