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Compare/Llama 3.1 Instruct 70B vs Hy3

Llama 3.1 Instruct 70BvsHy3

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

Meta

Llama 3.1 Instruct 70B

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

Hy3

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

Winner by Category

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

Pricing Comparison

MetricLlama 3.1 Instruct 70BHy3
Input ($/M tokens)$0.56$0.14
Output ($/M tokens)$0.56$0.58
Cost for 1M input + 100K output tokens:
Llama 3.1 Instruct 70B$0.62
Hy3$0.20

Speed Comparison

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

Editorial Analysis

Verdict. Hy3 takes the aggregate benchmark matchup 2–0 across 2 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, 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. Llama 3.1 Instruct 70B is strongest on Intelligence Index (6.6). Hy3 leads on Coding Index (58.8), Intelligence Index (25.8).

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. Meta and Tencent sell to overlapping but distinct developer audiences: Meta tends to ship frontier reasoning models with premium positioning, while Tencent 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): Llama 3.1 Instruct 70B costs $25.20 ($302/year); Hy3 costs $12.90 ($155/year). At a smaller 5M-input/2M-output scale (single-developer tool or prototype): Llama 3.1 Instruct 70B ≈ $3.92/run, Hy3 ≈ $1.86/run. At agent/realtime scale (200M input / 100M output per million requests): Llama 3.1 Instruct 70B ≈ $168/run, Hy3 ≈ $86/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
6.625.8
Coding Index
—58.8
Math Index
——
GPQA Diamond
——
MMLU-Pro
——
LiveCodeBench
——
AIME 2025
——
MATH-500
——
Humanity's Last Exam
——
SciCode
——
IFBench
——
TerminalBench
——
Llama 3.1 Instruct 70B0 wins
2 winsHy3

Frequently Asked Questions

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

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. Llama 3.1 Instruct 70B also has lower time-to-first-token (1.76s vs 2.71s).

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

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.