Instruction following · OpenRouter

Auto Max on IFEval: score, rank and what it means

Auto Max scores 78.1 on IFEval, placing it #366 of 600 models in the index. The benchmark average is 78.6 and the leader is Claude Opus 4.5 Pro at 96.1.

Score
78.1
0–100 scale
Rank
#366
of 600
Percentile
39th
within the index
Benchmark avg
78.6
all models
Leader
96.1
Claude Opus 4.5 Pro
Gap to leader
18.0
points

Score distribution

The chart shows the top 10 models on IFEval, with Auto Max highlighted. Longer bars mean higher scores.

Claude Opus 4.5 Pro 96.1
Claude Opus 4.5 Reasoning 95.9
GPT-5.2 Pro 95.6
GPT-5.2 Max 95.2
GPT-5.2 Reasoning 95.0
GPT-5.1 Pro 94.8
Gemini 3 Pro Max 94.7
GPT-5.1 Reasoning 94.6
Claude Opus 4.5 Max 94.5
o4 Reasoning 94.5

Top 10 leaderboard

#ModelProviderContextInput / 1MAvg score
1 Claude Opus 4.5 Pro Anthropic 200000 $20.98 89.1
2 Claude Opus 4.5 Reasoning Anthropic 2000000 $20.91 88.2
3 GPT-5.2 Pro OpenAI 2000000 $21.32 89.6
4 GPT-5.2 Max OpenAI 1000000 $21.39 89.2
5 GPT-5.2 Reasoning OpenAI 1000000 $20.98 87.5
6 GPT-5.1 Pro OpenAI 200000 $19.77 87.8
7 Gemini 3 Pro Max Google DeepMind 2000000 $20.57 87.9
8 GPT-5.1 Reasoning OpenAI 400000 $20.27 88.3
9 Claude Opus 4.5 Max Anthropic 1000000 $20.90 87.8
10 o4 Reasoning OpenAI 1000000 $19.69 87.5

What this score means

On IFEval, Auto Max sits at #366 of 600. The leader, Claude Opus 4.5 Pro, scores 96.1, so the gap to the top is 18.0 points. The median model in this index scores 81.2, which puts Auto Max below the midpoint.

OpenRouter models average 77.2 on this benchmark. Auto Max is 0.9 points above that provider line, so it is a stronger result than the average OpenRouter model.

Among mid-range models, the average is 76.5. Auto Max is 1.6 points above that group. This is the more useful comparison if you are shortlisting within the same tier rather than across the whole index.

Read a 78.1 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 $8.41 per million input tokens, Auto Max is above the median input price of $4.00 across the 600 models scored on IFEval. The models immediately around it in the ranking are shown below so you can compare score and price together.

ModelProviderContextInput / 1MAvg score
Auto Reasoning OpenRouter 65536 $8.39 71.5
Claude Haiku 4.5 Nano Anthropic 8192 $6.47 68.7
Reka Core Mini Reka AI 8192 $7.48 70.1
o3 Nano OpenAI 32768 $7.78 70.6
Auto Max OpenRouter 8192 $8.41 71.2
Firesearch Fireworks AI 32768 $7.03 68.5
Firesearch Max Fireworks AI 8192 $7.80 69.9

Other benchmarks for Auto Max

BenchmarkScoreRankPercentileRelative
MMLU-Pro 74.5 342 43th
GPQA Diamond 69.4 280 53th
SWE-bench Verified 58.7 345 43th
HumanEval 73.7 360 40th
MATH-500 72.6 361 40th
AIME 2025 68.5 287 52th
LiveCodeBench 60.0 368 39th
TruthfulQA 77.5 267 56th
HellaSwag 83.5 302 50th
MMMU 66.2 367 39th
Arena Elo 1365.1 331 45th

FAQ

What score does Auto Max get on IFEval?

Auto Max scores 78.1 on IFEval in this index. The benchmark average is 78.6 and the top score is 96.1.

How does Auto Max rank on IFEval?

It ranks #366 of 600 models, in the 39th percentile. The leader is Claude Opus 4.5 Pro at 96.1.

Is Auto Max good at IFEval?

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 IFEval score calculated?

IFEval is a instruction following 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 Auto Max cost?

Auto Max costs $8.41 per million input tokens and $40.47 per million output tokens.

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