Pairwise benchmark snapshot · Aug 17, 2026noindex (thin pair)

Tencent: Hunyuan A13B Instruct vs OpenAI o1-mini benchmark

Name: Tencent: Hunyuan A13B Instruct vs OpenAI o1-mini AI benchmark comparison
Creator: CompareLLM
License: https://creativecommons.org/licenses/by/4.0/

This page compares Tencent: Hunyuan A13B Instruct (tencent) and OpenAI o1-mini (OpenAI) using the latest snapshots we have as of Aug 17, 2026. Tencent: Hunyuan A13B Instruct wins on output price at $0.57/1M. Tencent: Hunyuan A13B Instruct has the larger context window (131k tokens). Every cell below is a dated snapshot from a named public source — we do not invent missing scores, and we do not run SWE-bench ourselves.

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tencent

Tencent: Hunyuan A13B Instruct

Auto-discovered from OpenRouter (tencent/hunyuan-a13b-instruct). Preview until a second source matches.

$0.5700000000000001/1M out

OpenAI

OpenAI o1-mini

OpenAI high-speed, cost-effective reasoning model optimized for STEM, math, and code generation.

Elo 1,445$4.4/1M out

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Model A

Model B

Quick vs:vs Claude Opus 4.5 vs Claude Opus 4.6 vs Claude Sonnet 4.5 vs Claude 3.7 Sonnet

Interactive Comparison Diagram

Matchup Breakdown

Tug-of-War Matchup Matrix

Category wins across intelligence, speed, and pricing efficiency.

Tencent: Hunyuan A13B Instruct (3)vsOpenAI o1-mini (7)

Tencent: Hunyuan A13B Instruct: 3W (30%)Overall: OpenAI o1-miniOpenAI o1-mini: 7W (70%)

← Tencent: Hunyuan A13B InstructOpenAI o1-mini →

OpenAI o1-mini (5/5)

Intelligence & Reasoning

Preference Elo, Coding proficiency, SWE-bench & LiveBench accuracy

Preference Elo

—vs1,445

Coding Elo

—vs1,468

SWE-bench

—vs56.4%

LiveBench

—vs62%

GPQA Diamond

—vs76.8%

Tencent: Hunyuan A13B Instruct: 0WOpenAI o1-mini: 5W

OpenAI o1-mini (2/2)

Speed & Latency

Generation throughput and time to first token responsiveness

Output speed

—vs85 tok/s

Time to first token

—vs280 ms

Tencent: Hunyuan A13B Instruct: 0WOpenAI o1-mini: 2W

Tencent: Hunyuan A13B Instruct (3/3)

Pricing & Capacity

Cost per million tokens and max context window length

Output price

$0.57/1Mvs$4.4/1M

Input price

$0.14/1Mvs$1.1/1M

Context window

131kvs128k

Tencent: Hunyuan A13B Instruct: 3WOpenAI o1-mini: 0W

Capability Matchup Radar

Multi-Dimensional Capability Radar

Each spoke is a skill. Farther from the center is better (0–100th percentile). Tap any dot to inspect details.

Tap any node to inspect

Percentile 0–100

Dimensional AdvantageOpenAI o1-mini 4/6

Preference Elo

No shared data

Throughput Speed

No shared data

Token Price Efficiency

Tencent: Hunyuan A13B Instruct

$3.83/1M cheaper

Full Benchmark Score Matrix

—

Elo

High is better

—

EloHigh is better

1,445

Code Elo

High is better

—

Code EloHigh is better

1,468

LiveBench

High is better

—

LiveBenchHigh is better

62%

SWE-bench

High is better

—

SWE-benchHigh is better

56.4%

GPQA

High is better

—

GPQAHigh is better

76.8%

TTFT

Low is better

—

TTFTLow is better

280 ms

Speed

High is better

—

SpeedHigh is better

85 tok/s

In $

Low is better

+686%$0.14 / 1M

In $Low is better

$1.10 / 1M

Out $

Low is better

+672%$0.57 / 1M

Out $Low is better

$4.40 / 1M

Context

High is better

+2%131k

ContextHigh is better

128k

Interactive Simulator (USD)

Workload Cost & Savings Calculator

Simulate monthly production API costs in USD (US Dollar).

Save up to 87% with Tencent: Hunyuan A13B Instruct

Monthly Volume50M tokens/mo

Quick Presets:

Token Ratio (In vs Out)70% In / 30% Out

RAG / Search (10% out)Coding / Chat (50% out)

Tencent: Hunyuan A13B Instruct$13.45 / mo

In: $4.9Out: $8.55

OpenAI o1-mini$104.50 / mo

In: $38.5Out: $66

Estimated Cost Delta

Tencent: Hunyuan A13B Instruct is estimated to save $91.05/month ($1,093/year).

Based on 50M tokens (30% gen)

Key Selection Recommendations

1
Tencent: Hunyuan A13B Instruct:Pick Tencent: Hunyuan A13B Instruct when you are optimizing output cost.

Recommended Workload Routing

Repo / coding agentsinsufficient data

Need SWE-bench on both sides.

High-volume chatTencent: Hunyuan A13B Instruct

Lower output list price ($0.57/1M).

Voice / low-latency UIinsufficient data

Need TTFT on both sides.

Long-document RAGTencent: Hunyuan A13B Instruct

Larger window (131k).

Screenshots / visionOpenAI o1-mini

OpenAI o1-mini is the side marked multimodal in the catalog.

Target Workload	Recommended Pick	Evaluation Rationale
Repo / coding agents	insufficient data	Need SWE-bench on both sides.
High-volume chat	Tencent: Hunyuan A13B Instruct	Lower output list price ($0.57/1M).
Voice / low-latency UI	insufficient data	Need TTFT on both sides.
Long-document RAG	Tencent: Hunyuan A13B Instruct	Larger window (131k).
Screenshots / vision	OpenAI o1-mini	OpenAI o1-mini is the side marked multimodal in the catalog.

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LIVE

tencent

Tencent: Hunyuan A13B Instruct

Elo n/a

LiveBench—

SWE-bench—

Speed—

Output cost$0.57/1M

OpenAI

OpenAI o1-mini

Elo 1,445

LiveBench62%

SWE-bench56.4%

Speed85 tok/s

Output cost$4.4/1M

Frequently Asked Questions

Which is better overall, Tencent: Hunyuan A13B Instruct or OpenAI o1-mini?: We do not have preference Elo for both models, so we do not declare an overall winner. Compare the metrics that exist.
Which is better at coding, Tencent: Hunyuan A13B Instruct or OpenAI o1-mini?: SWE-bench is missing for at least one model, so we do not rank coding from a single number.
Which is cheaper to run in production?: Tencent: Hunyuan A13B Instruct output tokens are $0.57/1M versus $4.4/1M. Input prices and retry rates still move the real bill.
Which is faster, Tencent: Hunyuan A13B Instruct or OpenAI o1-mini?: We do not have TTFT for both models.
Which has the larger context window?: Tencent: Hunyuan A13B Instruct accepts 131k tokens versus 128k.
Can I self-host either model?: Neither model is marked open-weights here. You are comparing hosted APIs.
Are these scores from CompareLLM’s own evals?: No. V1 aggregates public leaderboards (and optional first-party latency pings). Each cell names its source and date. Read /methodology.
What does preference Elo mean on this page?: Preference Elo is a crowd vote from LMArena / Arena. People see two hidden answers and pick the one they like more. The model that wins more often gets a higher Elo. That means people preferred it — not that it passed a school test. It is not SWE-bench, not accuracy, and not a number we invent. Tencent: Hunyuan A13B Instruct and OpenAI o1-mini Elo cells are dated snapshots from the named source — we do not compute Arena ourselves.

Similar Head-to-Head Comparisons

All Tencent: Hunyuan A13B Instruct matchups →|All OpenAI o1-mini matchups →

OpenAI o1-mini vs GPT-4o mini (previous gpt-mini)OpenAI o1-mini vs OpenAI: o3 Mini (next gpt-mini)GPT-5 vs OpenAI o1-mini GPT-4.5 Orion vs OpenAI o1-mini GPT-5.6 Sol vs OpenAI o1-mini GPT-5.6 Terra vs OpenAI o1-mini

Tencent: Hunyuan A13B Instruct vs OpenAI o1-mini benchmark

Interactive Comparison Diagram

Matchup Breakdown

Tug-of-War Matchup Matrix

Category wins across intelligence, speed, and pricing efficiency.

Tencent: Hunyuan A13B Instruct (3)vsOpenAI o1-mini (7)

Tencent: Hunyuan A13B Instruct: 3W (30%)Overall: OpenAI o1-miniOpenAI o1-mini: 7W (70%)

← Tencent: Hunyuan A13B InstructOpenAI o1-mini →

OpenAI o1-mini (5/5)

Intelligence & Reasoning

Preference Elo, Coding proficiency, SWE-bench & LiveBench accuracy

Preference Elo

—vs1,445

Coding Elo

—vs1,468

SWE-bench

—vs56.4%

LiveBench

—vs62%

GPQA Diamond

—vs76.8%

Tencent: Hunyuan A13B Instruct: 0WOpenAI o1-mini: 5W

OpenAI o1-mini (2/2)

Speed & Latency

Generation throughput and time to first token responsiveness

Output speed

—vs85 tok/s

Time to first token

—vs280 ms

Tencent: Hunyuan A13B Instruct: 0WOpenAI o1-mini: 2W

Tencent: Hunyuan A13B Instruct (3/3)

Pricing & Capacity

Cost per million tokens and max context window length

Output price

$0.57/1Mvs$4.4/1M

Input price

$0.14/1Mvs$1.1/1M

Context window

131kvs128k

Tencent: Hunyuan A13B Instruct: 3WOpenAI o1-mini: 0W

Recommended Workload Routing

Repo / coding agentsinsufficient data

Need SWE-bench on both sides.

High-volume chatTencent: Hunyuan A13B Instruct

Lower output list price ($0.57/1M).

Voice / low-latency UIinsufficient data

Need TTFT on both sides.

Long-document RAGTencent: Hunyuan A13B Instruct

Larger window (131k).

Screenshots / visionOpenAI o1-mini

OpenAI o1-mini is the side marked multimodal in the catalog.

Target Workload	Recommended Pick	Evaluation Rationale
Repo / coding agents	insufficient data	Need SWE-bench on both sides.
High-volume chat	Tencent: Hunyuan A13B Instruct	Lower output list price ($0.57/1M).
Voice / low-latency UI	insufficient data	Need TTFT on both sides.
Long-document RAG	Tencent: Hunyuan A13B Instruct	Larger window (131k).
Screenshots / vision	OpenAI o1-mini	OpenAI o1-mini is the side marked multimodal in the catalog.

Frequently Asked Questions

Which is better overall, Tencent: Hunyuan A13B Instruct or OpenAI o1-mini?

We do not have preference Elo for both models, so we do not declare an overall winner. Compare the metrics that exist.

Which is better at coding, Tencent: Hunyuan A13B Instruct or OpenAI o1-mini?

SWE-bench is missing for at least one model, so we do not rank coding from a single number.

Which is cheaper to run in production?

Tencent: Hunyuan A13B Instruct output tokens are $0.57/1M versus $4.4/1M. Input prices and retry rates still move the real bill.

Which is faster, Tencent: Hunyuan A13B Instruct or OpenAI o1-mini?

We do not have TTFT for both models.

Which has the larger context window?

Tencent: Hunyuan A13B Instruct accepts 131k tokens versus 128k.

Can I self-host either model?

Neither model is marked open-weights here. You are comparing hosted APIs.

Are these scores from CompareLLM’s own evals?

No. V1 aggregates public leaderboards (and optional first-party latency pings). Each cell names its source and date. Read /methodology.

What does preference Elo mean on this page?

Preference Elo is a crowd vote from LMArena / Arena. People see two hidden answers and pick the one they like more. The model that wins more often gets a higher Elo. That means people preferred it — not that it passed a school test. It is not SWE-bench, not accuracy, and not a number we invent. Tencent: Hunyuan A13B Instruct and OpenAI o1-mini Elo cells are dated snapshots from the named source — we do not compute Arena ourselves.