Compare/Qwen3.5 27B (Reasoning) vs Nova 2.0 Omni (Non-reasoning)

Qwen3.5 27B (Reasoning)vsNova 2.0 Omni (Non-reasoning)

Side-by-side comparison of pricing, 12 benchmarks, and generation speed.

Alibaba

Qwen3.5 27B (Reasoning)

Input
$0.3/M
Output
$2.4/M
Speed
77 tok/s
TTFT
5.58s
Amazon

Nova 2.0 Omni (Non-reasoning)

Input
$0.3/M
Output
$2.5/M
Speed
TTFT

Winner by Category

Cheaper
Qwen3.5 27B (Reasoning)
Faster (tok/s)
Qwen3.5 27B (Reasoning)
Lower Latency
Qwen3.5 27B (Reasoning)
Benchmarks (1-0)
Qwen3.5 27B (Reasoning)

Pricing Comparison

MetricQwen3.5 27B (Reasoning)Nova 2.0 Omni (Non-reasoning)
Input ($/M tokens)$0.3$0.3
Output ($/M tokens)$2.4$2.5
Cost for 1M input + 100K output tokens:
Qwen3.5 27B (Reasoning)$0.54
Nova 2.0 Omni (Non-reasoning)$0.55

Speed Comparison

Output Speed (tokens/s) — higher is better
Qwen3.5 27B (Reasoning)
77 tok/s
Nova 2.0 Omni (Non-reasoning)
Time to First Token (seconds) — lower is better
Qwen3.5 27B (Reasoning)
5.58s
Nova 2.0 Omni (Non-reasoning)

Editorial Analysis

Verdict. Qwen3.5 27B (Reasoning) wins the overall benchmark matchup 1–0 across 1 overlapping categories, but raw benchmark score is only one input to the decision.

Pricing. Both models sit in the budget bracket for output-token pricing. At 1.0× the per-million-token cost, Qwen3.5 27B (Reasoning) is meaningfully cheaper if your traffic is output-heavy (long completions, document generation, agent loops). Qwen3.5 27B (Reasoning) makes more sense when output volume is low and absolute reasoning quality justifies the premium.

Strengths. Qwen3.5 27B (Reasoning) is strongest on Intelligence Index (34.6). Nova 2.0 Omni (Non-reasoning) leads on Intelligence Index (10.4).

Speed. Speed data is incomplete for this pair; benchmark and price should decide.

Provider. Alibaba and Amazon sell to overlapping but distinct developer audiences: Alibaba tends to ship frontier reasoning models with premium positioning, while Amazon often prices more aggressively. Your existing vendor relationships, billing, and SLA preferences may matter as much as the raw numbers above.

Workload cost. Workload scenarios (per million requests at 30M input + 15M output tokens): Qwen3.5 27B (Reasoning) costs $45.00 ($540/year); Nova 2.0 Omni (Non-reasoning) costs $46.50 ($558/year). At a smaller 5M-input/2M-output scale (single-developer tool or prototype): Qwen3.5 27B (Reasoning) ≈ $6.30/run, Nova 2.0 Omni (Non-reasoning) ≈ $6.50/run. At agent/realtime scale (200M input / 100M output per million requests): Qwen3.5 27B (Reasoning) ≈ $300/run, Nova 2.0 Omni (Non-reasoning) ≈ $310/run. Qwen3.5 27B (Reasoning) becomes more attractive at higher volume — the absolute per-token pricing difference compounds when you ship at scale.

Recommendation. Both models have legitimate use cases — the right answer depends on whether you are optimizing for benchmark ceiling, latency, or unit cost. Start with the cheaper / faster model, evaluate against your specific task, and only switch if the upgrade shows a meaningful lift.

Benchmark Comparison

Data from Artificial Analysis API — 12 benchmarks

Intelligence Index
34.610.4
Coding Index
Math Index
GPQA Diamond
MMLU-Pro
LiveCodeBench
AIME 2025
MATH-500
Humanity's Last Exam
SciCode
IFBench
TerminalBench
Qwen3.5 27B (Reasoning)1 wins
0 winsNova 2.0 Omni (Non-reasoning)

Frequently Asked Questions

Which is cheaper, Qwen3.5 27B (Reasoning) or Nova 2.0 Omni (Non-reasoning)?

Qwen3.5 27B (Reasoning) is cheaper overall. Its blended price (3:1 input/output ratio) is $0.82/M tokens vs $0.85/M for Nova 2.0 Omni (Non-reasoning).

Which model performs better on benchmarks?

Qwen3.5 27B (Reasoning) wins 1 out of 12 benchmarks compared to 0 for Nova 2.0 Omni (Non-reasoning). See the detailed benchmark chart above for per-category results.

Which is faster for real-time applications?

Qwen3.5 27B (Reasoning) generates tokens faster at 77 tok/s vs — tok/s. Qwen3.5 27B (Reasoning) also has lower time-to-first-token (5.58s vs —s).

When should I use Qwen3.5 27B (Reasoning) vs Nova 2.0 Omni (Non-reasoning)?

Choose based on your priorities: Qwen3.5 27B (Reasoning) for lower cost, Qwen3.5 27B (Reasoning) for stronger benchmark performance, and Qwen3.5 27B (Reasoning) for faster generation. For latency-sensitive apps, check the TTFT comparison above.