Side-by-side comparison of pricing, 12 benchmarks, and generation speed.
| Metric | HyperNova 60B 2605 (high, based on gpt-oss-120b) | Qwen3.5 4B (Reasoning) |
|---|---|---|
| Input ($/M tokens) | $0.04 | $0.03 |
| Output ($/M tokens) | $0.14 | $0.15 |
Verdict. HyperNova 60B 2605 (high, based on gpt-oss-120b) and Qwen3.5 4B (Reasoning) split the benchmark comparison evenly at 1–1. The tiebreaker here is price, speed, and what you actually run them on.
Pricing. Both models sit in the budget bracket for output-token pricing. At 0.9× the per-million-token cost, HyperNova 60B 2605 (high, based on gpt-oss-120b) is meaningfully cheaper if your traffic is output-heavy (long completions, document generation, agent loops). HyperNova 60B 2605 (high, based on gpt-oss-120b) makes more sense when output volume is low and absolute reasoning quality justifies the premium.
Strengths. HyperNova 60B 2605 (high, based on gpt-oss-120b) is strongest on Coding Index (23.2), Intelligence Index (18.3). Qwen3.5 4B (Reasoning) leads on Coding Index (22.6), Intelligence Index (20.4).
Speed. On throughput, HyperNova 60B 2605 (high, based on gpt-oss-120b) generates tokens at 350 tok/s versus 24 tok/s — about 93% faster. On time-to-first-token, Qwen3.5 4B (Reasoning) responds in 750ms vs 790ms, which matters most for chat-style UIs.
Provider. Multiverse Computing and Alibaba sell to overlapping but distinct developer audiences: Multiverse Computing tends to ship frontier reasoning models with premium positioning, while Alibaba 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): HyperNova 60B 2605 (high, based on gpt-oss-120b) costs $3.30 ($40/year); Qwen3.5 4B (Reasoning) costs $3.15 ($38/year). At a smaller 5M-input/2M-output scale (single-developer tool or prototype): HyperNova 60B 2605 (high, based on gpt-oss-120b) ≈ $0.48/run, Qwen3.5 4B (Reasoning) ≈ $0.45/run. At agent/realtime scale (200M input / 100M output per million requests): HyperNova 60B 2605 (high, based on gpt-oss-120b) ≈ $22/run, Qwen3.5 4B (Reasoning) ≈ $21/run. Qwen3.5 4B (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.
Head-to-head deltas
Data from Artificial Analysis API — 12 benchmarks
Qwen3.5 4B (Reasoning) is cheaper overall. Its blended price (3:1 input/output ratio) is $0.06/M tokens vs $0.07/M for HyperNova 60B 2605 (high, based on gpt-oss-120b).
It's a tie — both models win 1 benchmarks each across 12 evaluated categories. See the detailed benchmark chart above for per-category results.
HyperNova 60B 2605 (high, based on gpt-oss-120b) generates tokens faster at 350 tok/s vs 24 tok/s. However, Qwen3.5 4B (Reasoning) has lower time-to-first-token (0.75s vs 0.79s).
Choose based on your priorities: Qwen3.5 4B (Reasoning) for lower cost, both perform similarly on benchmarks, and HyperNova 60B 2605 (high, based on gpt-oss-120b) for faster generation. For latency-sensitive apps, check the TTFT comparison above.