Commonsense · MiniMax

MiniMax-Text 1.5B on HellaSwag: score, rank and what it means

MiniMax-Text 1.5B scores 68.5 on HellaSwag, placing it #553 of 600 models in the index. The benchmark average is 81.4 and the leader is GPT-5.2 Max at 96.1.

Score
68.5
0–100 scale
Rank
#553
of 600
Percentile
8th
within the index
Benchmark avg
81.4
all models
Leader
96.1
GPT-5.2 Max
Gap to leader
27.6
points

Score distribution

The chart shows the top 10 models on HellaSwag, with MiniMax-Text 1.5B highlighted. Longer bars mean higher scores.

GPT-5.2 Max 96.1
GPT-5.2 Turbo 95.5
GPT-5.2 Pro 95.3
Claude Opus 4.5 Pro 95.2
Claude Sonnet 4.5 Reasoning 95.2
Grok 4 Reasoning 95.2
GPT-5.2 Vision 94.6
Gemini 3 Pro Turbo 94.6
GPT-5.1 Reasoning 94.4
o4 Pro 94.4

Top 10 leaderboard

#ModelProviderContextInput / 1MAvg score
1 GPT-5.2 Max OpenAI 1000000 $21.39 89.2
2 GPT-5.2 Turbo OpenAI 1000000 $20.73 87.4
3 GPT-5.2 Pro OpenAI 2000000 $21.32 89.6
4 Claude Opus 4.5 Pro Anthropic 200000 $20.98 89.1
5 Claude Sonnet 4.5 Reasoning Anthropic 400000 $19.48 87.7
6 Grok 4 Reasoning xAI 2000000 $19.67 87.8
7 GPT-5.2 Vision OpenAI 1000000 $19.03 87.4
8 Gemini 3 Pro Turbo Google DeepMind 400000 $19.62 86.4
9 GPT-5.1 Reasoning OpenAI 400000 $20.27 88.3
10 o4 Pro OpenAI 1000000 $19.37 87.3

What this score means

On HellaSwag, MiniMax-Text 1.5B sits at #553 of 600. The leader, GPT-5.2 Max, scores 96.1, so the gap to the top is 27.6 points. The median model in this index scores 83.6, which puts MiniMax-Text 1.5B below the midpoint.

MiniMax models average 81.3 on this benchmark. MiniMax-Text 1.5B is 12.8 points below that provider line, so it is a weaker result than the average MiniMax model.

Among small open-weight models, the average is 70.2. MiniMax-Text 1.5B is 1.7 points below that group. This is the more useful comparison if you are shortlisting within the same tier rather than across the whole index.

Read a 68.5 as a relative signal, not an absolute guarantee. Benchmark scores depend on prompt format, evaluation harness and contamination controls. Use this page to narrow the shortlist, then test the model on your own data.

Price context

At $0.58 per million input tokens, MiniMax-Text 1.5B is below the median input price of $4.00 across the 600 models scored on HellaSwag. The models immediately around it in the ranking are shown below so you can compare score and price together.

ModelProviderContextInput / 1MAvg score
Codestral 1.5B Mistral AI 8192 $0.52 49.9
Llama 3.3 1.5B Meta AI 4096 $0.61 52.2
Nemotron Nano 8B NVIDIA 8192 $0.46 48.1
Llama 3.1 Cerebras 1.5B Cerebras 4096 $0.48 50.2
MiniMax-Text 1.5B MiniMax 32768 $0.58 51.5
Mistral Small 3 1.5B Mistral AI 32768 $0.42 49.2
Qwen3-Coder 1.5B Alibaba Cloud 32768 $0.76 52.8

Other benchmarks for MiniMax-Text 1.5B

BenchmarkScoreRankPercentileRelative
MMLU-Pro 58.0 550 8th
GPQA Diamond 46.5 553 8th
SWE-bench Verified 36.1 546 9th
HumanEval 54.1 548 9th
MATH-500 54.0 527 12th
AIME 2025 38.1 550 8th
LiveCodeBench 40.2 537 11th
IFEval 63.4 543 10th
TruthfulQA 58.0 548 9th
MMMU 49.4 556 7th
Arena Elo 1204.8 548 9th

FAQ

What score does MiniMax-Text 1.5B get on HellaSwag?

MiniMax-Text 1.5B scores 68.5 on HellaSwag in this index. The benchmark average is 81.4 and the top score is 96.1.

How does MiniMax-Text 1.5B rank on HellaSwag?

It ranks #553 of 600 models, in the 8th percentile. The leader is GPT-5.2 Max at 96.1.

Is MiniMax-Text 1.5B good at HellaSwag?

It is below the median for this benchmark, so test it carefully before relying on it for this capability. The result should be read alongside its price and context window.

How is the HellaSwag score calculated?

HellaSwag is a commonsense benchmark. Scores in this index are modelled estimates on a 0–100 scale (or Elo for Arena), derived from capability tier and benchmark difficulty. They are not official leaderboard results.

What does MiniMax-Text 1.5B cost?

MiniMax-Text 1.5B costs $0.58 per million input tokens and $2.90 per million output tokens.

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