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Compare/gpt-oss-120b (low) vs Hy3

gpt-oss-120b (low)vsHy3

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

OpenAI

gpt-oss-120b (low)

Input
$0.15/M
Output
$0.54/M
Speed
240 tok/s
TTFT
0.81s
Tencent

Hy3

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

Winner by Category

Cheaper
gpt-oss-120b (low)
Faster (tok/s)
gpt-oss-120b (low)
Lower Latency
gpt-oss-120b (low)
Benchmarks (0-2)
Hy3

Pricing Comparison

Metricgpt-oss-120b (low)Hy3
Input ($/M tokens)$0.15$0.14
Output ($/M tokens)$0.54$0.58
Cost for 1M input + 100K output tokens:
gpt-oss-120b (low)$0.20
Hy3$0.20

Speed Comparison

Output Speed (tokens/s) — higher is better
gpt-oss-120b (low)
240 tok/s
Hy3
91 tok/s
Time to First Token (seconds) — lower is better
gpt-oss-120b (low)
0.81s
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 0.9× the per-million-token cost, gpt-oss-120b (low) is meaningfully cheaper if your traffic is output-heavy (long completions, document generation, agent loops). gpt-oss-120b (low) makes more sense when output volume is low and absolute reasoning quality justifies the premium.

Strengths. gpt-oss-120b (low) is strongest on Coding Index (21.2), Intelligence Index (10.2). Hy3 leads on Coding Index (58.8), Intelligence Index (25.8).

Speed. On throughput, gpt-oss-120b (low) generates tokens at 240 tok/s versus 91 tok/s — about 62% faster. On time-to-first-token, gpt-oss-120b (low) responds in 810ms vs 2710ms, which matters most for chat-style UIs.

Provider. OpenAI and Tencent sell to overlapping but distinct developer audiences: OpenAI 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): gpt-oss-120b (low) costs $12.60 ($151/year); Hy3 costs $12.90 ($155/year). At a smaller 5M-input/2M-output scale (single-developer tool or prototype): gpt-oss-120b (low) ≈ $1.83/run, Hy3 ≈ $1.86/run. At agent/realtime scale (200M input / 100M output per million requests): gpt-oss-120b (low) ≈ $84/run, Hy3 ≈ $86/run. gpt-oss-120b (low) 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

  • On throughput, gpt-oss-120b (low) is 2.64× faster (240 tok/s vs 91 tok/s). For streaming chat or real-time agents this alone often flips the recommendation.

Benchmark Comparison

Data from Artificial Analysis API — 12 benchmarks

Intelligence Index
10.225.8
Coding Index
21.258.8
Math Index
——
GPQA Diamond
——
MMLU-Pro
——
LiveCodeBench
——
AIME 2025
——
MATH-500
——
Humanity's Last Exam
——
SciCode
——
IFBench
——
TerminalBench
——
gpt-oss-120b (low)0 wins
2 winsHy3

Frequently Asked Questions

Which is cheaper, gpt-oss-120b (low) or Hy3?

gpt-oss-120b (low) is cheaper overall. Its blended price (3:1 input/output ratio) is $0.25/M tokens vs $0.25/M for Hy3.

Which model performs better on benchmarks?

Hy3 wins 2 out of 12 benchmarks compared to 0 for gpt-oss-120b (low). See the detailed benchmark chart above for per-category results.

Which is faster for real-time applications?

gpt-oss-120b (low) generates tokens faster at 240 tok/s vs 91 tok/s. gpt-oss-120b (low) also has lower time-to-first-token (0.81s vs 2.71s).

When should I use gpt-oss-120b (low) vs Hy3?

Choose based on your priorities: gpt-oss-120b (low) for lower cost, Hy3 for stronger benchmark performance, and gpt-oss-120b (low) for faster generation. For latency-sensitive apps, check the TTFT comparison above.