Model Comparison
Qwen3 VL 235B A22B Instruct
vs. Tiny Aya Global
Comparing 2 AI models · 10 benchmarks · Alibaba, Cohere
Recommended Pick
Al Qwen3 VL 235B A22B Instruct 10 metric wins Strongest on: Reasoning, Intelligence, Coding
Lowest Price
Tiny Aya Global
$0.00/1M input price
Best Reasoning
Qwen3 VL 235B A22B Instruct
47.9 reasoning score
Blends available reasoning benchmarks
Best for Coding
Qwen3 VL 235B A22B Instruct
16.5 coding index
Composite Indices
Higher is better; speed and price are normalized
Standard Benchmarks
Only benchmarks with data are shown
Differences That Matter
Price gap
Tiny Aya Global is ∞x cheaper on input tokens than Qwen3 VL 235B A22B Instruct.
Speed gap
Tiny Aya Global generates about 2.3x as many tokens per second as Qwen3 VL 235B A22B Instruct.
Reasoning gap
Qwen3 VL 235B A22B Instruct leads Tiny Aya Global by 34.5 points on reasoning.
Coding gap
Qwen3 VL 235B A22B Instruct leads Tiny Aya Global by 15.3 points on coding.
Top-pick rationale
Qwen3 VL 235B A22B Instruct wins 10 measurable categories, including Reasoning, Intelligence, Coding, GPQA.
Response Face-Off
Run one prompt through the selected models and compare response quality with live speed and cost context.
Qwen3 VL 235B A22B Instruct
Alibaba
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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Tiny Aya Global
Cohere
TTFT
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Time
—
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 Al Qwen3 VL 235B A22B Instruct | Co Tiny Aya Global |
|---|---|---|
| Pricing per 1M tokens | ||
| Input Cost | $0.30/1M | $0.00/1M |
| Output Cost | $1.90/1M | $0.00/1M |
| Blended (3:1) | $0.70/1M | — |
| Specifications | ||
| Organization | Alibaba | Cohere |
| Release Date | Sep 23, 2025 | Feb 17, 2026 |
| Performance & Speed | ||
| Throughput | 53.5 tok/s | 125.2 tok/s |
| TTFT | 1090ms | 243ms |
| Latency | 1090ms | 243ms |
| Composite Indices | ||
| Value Score | 100.0 | — |
| Reasoning Score | 47.9 | 13.5 |
| Intelligence | 20.8 | 4.7 |
| Coding | 16.5 | 1.2 |
| Math | 70.7 | — |
| Standard Benchmarks | ||
| GPQA | 71.2% | 30.5% |
| MMLU Pro | 82.3% | — |
| HLE | 6.3% | 5.2% |
| LiveCodeBench | 59.4% | — |
| AIME 2025 | 70.7% | — |
| SciCode | 35.9% | 3.6% |
| LCR | 31.7% | 0.0% |
| IFBench | 42.7% | 20.1% |
| TAU-bench v2 | 35.1% | 0.0% |
| TerminalBench Hard | 6.8% | 0.0% |
Key Takeaways
Tiny Aya Global offers the best value at $0.00/1M, making it ideal for high-volume applications and cost-conscious projects.
Qwen3 VL 235B A22B Instruct has the strongest reasoning profile with a 47.9 reasoning score, combining the available reasoning-heavy benchmarks.
Qwen3 VL 235B A22B Instruct reaches a 16.5 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
Qwen3 VL 235B A22B Instruct
- Complex reasoning tasks
- Research & analysis
- Code generation
- Software development
Tiny Aya Global
- Cost-sensitive applications
- High-volume processing
