Side-by-side comparison of pricing, 12 benchmarks, and generation speed.
| Metric | Hy3 | Llama 3.1 Instruct 70B |
|---|---|---|
| Input ($/M tokens) | $0.136 | $0.56 |
| Output ($/M tokens) | $0.557 | $0.56 |
Verdict. Llama 3.1 Instruct 70B takes the aggregate benchmark matchup 7–5 across 12 categories. Real workloads usually care about a handful of specific tasks — see the per-benchmark table above.
Pricing. Both models sit in the budget bracket for output-token pricing. At 1.0× the per-million-token cost, Hy3 is meaningfully cheaper if your traffic is output-heavy (long completions, document generation, agent loops). Hy3 makes more sense when output volume is low and absolute reasoning quality justifies the premium.
Strengths. Hy3 is strongest on GPQA Diamond (90%), Coding Index (58.8), SciCode (48%). Llama 3.1 Instruct 70B leads on MMLU-Pro (68%), MATH-500 (65%), GPQA Diamond (41%).
Speed. On throughput, Hy3 generates tokens at 71 tok/s versus 0 tok/s — about 100% faster. On time-to-first-token, Llama 3.1 Instruct 70B responds in 0ms vs 1757ms, which matters most for chat-style UIs.
Provider. Tencent and Meta sell to overlapping but distinct developer audiences: Tencent tends to ship frontier reasoning models with premium positioning, while Meta 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): Hy3 costs $12.44 ($149/year); Llama 3.1 Instruct 70B costs $25.20 ($302/year). At a smaller 5M-input/2M-output scale (single-developer tool or prototype): Hy3 ≈ $1.79/run, Llama 3.1 Instruct 70B ≈ $3.92/run. At agent/realtime scale (200M input / 100M output per million requests): Hy3 ≈ $83/run, Llama 3.1 Instruct 70B ≈ $168/run. Hy3 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
Hy3 is cheaper overall. Its blended price (3:1 input/output ratio) is $0.24/M tokens vs $0.56/M for Llama 3.1 Instruct 70B.
Llama 3.1 Instruct 70B wins 7 out of 12 benchmarks compared to 5 for Hy3. See the detailed benchmark chart above for per-category results.
Hy3 generates tokens faster at 71 tok/s vs 0 tok/s. However, Llama 3.1 Instruct 70B has lower time-to-first-token (0.00s vs 1.76s).
Choose based on your priorities: Hy3 for lower cost, Llama 3.1 Instruct 70B for stronger benchmark performance, and Hy3 for faster generation. For latency-sensitive apps, check the TTFT comparison above.