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Compare/Hy3 vs Llama 3.1 Instruct 70B

Hy3vsLlama 3.1 Instruct 70B

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

Tencent

Hy3

Input
$0.14/M
Output
$0.58/M
Speed
91 tok/s
TTFT
2.71s
Meta

Llama 3.1 Instruct 70B

Input
$0.56/M
Output
$0.56/M
Speed
70 tok/s
TTFT
1.76s

Winner by Category

Cheaper
Hy3
Faster (tok/s)
Hy3
Lower Latency
Llama 3.1 Instruct 70B
Benchmarks (2-0)
Hy3

Pricing Comparison

MetricHy3Llama 3.1 Instruct 70B
Input ($/M tokens)$0.14$0.56
Output ($/M tokens)$0.58$0.56
Cost for 1M input + 100K output tokens:
Hy3$0.20
Llama 3.1 Instruct 70B$0.62

Speed Comparison

Output Speed (tokens/s) — higher is better
Hy3
91 tok/s
Llama 3.1 Instruct 70B
70 tok/s
Time to First Token (seconds) — lower is better
Hy3
2.71s
Llama 3.1 Instruct 70B
1.76s

Editorial Analysis

Verdict. Hy3 wins the overall benchmark matchup 2–0 across 2 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, Llama 3.1 Instruct 70B is meaningfully cheaper if your traffic is output-heavy (long completions, document generation, agent loops). Llama 3.1 Instruct 70B makes more sense when output volume is low and absolute reasoning quality justifies the premium.

Strengths. Hy3 is strongest on Coding Index (58.8), Intelligence Index (25.8). Llama 3.1 Instruct 70B leads on Intelligence Index (6.6).

Speed. On throughput, Hy3 generates tokens at 91 tok/s versus 70 tok/s — about 23% faster. On time-to-first-token, Llama 3.1 Instruct 70B responds in 1760ms vs 2710ms, 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 $12.90 ($155/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 ≈ $1.86/run, Llama 3.1 Instruct 70B ≈ $3.92/run. At agent/realtime scale (200M input / 100M output per million requests): Hy3 ≈ $86/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.

Benchmark Comparison

Data from Artificial Analysis API — 12 benchmarks

Intelligence Index
25.86.6
Coding Index
58.8—
Math Index
——
GPQA Diamond
——
MMLU-Pro
——
LiveCodeBench
——
AIME 2025
——
MATH-500
——
Humanity's Last Exam
——
SciCode
——
IFBench
——
TerminalBench
——
Hy32 wins
0 winsLlama 3.1 Instruct 70B

Frequently Asked Questions

Which is cheaper, Hy3 or Llama 3.1 Instruct 70B?

Hy3 is cheaper overall. Its blended price (3:1 input/output ratio) is $0.25/M tokens vs $0.56/M for Llama 3.1 Instruct 70B.

Which model performs better on benchmarks?

Hy3 wins 2 out of 12 benchmarks compared to 0 for Llama 3.1 Instruct 70B. See the detailed benchmark chart above for per-category results.

Which is faster for real-time applications?

Hy3 generates tokens faster at 91 tok/s vs 70 tok/s. However, Llama 3.1 Instruct 70B has lower time-to-first-token (1.76s vs 2.71s).

When should I use Hy3 vs Llama 3.1 Instruct 70B?

Choose based on your priorities: Hy3 for lower cost, Hy3 for stronger benchmark performance, and Hy3 for faster generation. For latency-sensitive apps, check the TTFT comparison above.