Coding · Cerebras

Llama 3.1 Cerebras Base on SWE-bench Verified: score, rank and what it means

Llama 3.1 Cerebras Base scores 58.6 on SWE-bench Verified, placing it #347 of 600 models in the index. The benchmark average is 57.5 and the leader is GPT-5.2 Pro at 81.7.

Score
58.6
0–100 scale
Rank
#347
of 600
Percentile
42th
within the index
Benchmark avg
57.5
all models
Leader
81.7
GPT-5.2 Pro
Gap to leader
23.1
points

Score distribution

The chart shows the top 10 models on SWE-bench Verified, with Llama 3.1 Cerebras Base highlighted. Longer bars mean higher scores.

GPT-5.2 Pro 81.7
Claude Opus 4.5 Pro 81.1
GPT-5.2 Max 80.5
Claude Sonnet 4.5 Max 80.2
GPT-5.2 80.2
GPT-5.1 Pro 80.1
o4 Max 79.8
Claude Sonnet 4.5 Reasoning 79.6
Claude Opus 4.5 Max 79.5
Claude Opus 4.5 Reasoning 79.5

Top 10 leaderboard

#ModelProviderContextInput / 1MAvg score
1 GPT-5.2 Pro OpenAI 2000000 $21.32 89.6
2 Claude Opus 4.5 Pro Anthropic 200000 $20.98 89.1
3 GPT-5.2 Max OpenAI 1000000 $21.39 89.2
4 Claude Sonnet 4.5 Max Anthropic 1000000 $19.90 87.2
5 GPT-5.2 OpenAI 2000000 $19.71 88.0
6 GPT-5.1 Pro OpenAI 200000 $19.77 87.8
7 o4 Max OpenAI 2000000 $19.51 86.2
8 Claude Sonnet 4.5 Reasoning Anthropic 400000 $19.48 87.7
9 Claude Opus 4.5 Max Anthropic 1000000 $20.90 87.8
10 Claude Opus 4.5 Reasoning Anthropic 2000000 $20.91 88.2

What this score means

On SWE-bench Verified, Llama 3.1 Cerebras Base sits at #347 of 600. The leader, GPT-5.2 Pro, scores 81.7, so the gap to the top is 23.1 points. The median model in this index scores 61.0, which puts Llama 3.1 Cerebras Base below the midpoint.

Cerebras models average 53.4 on this benchmark. Llama 3.1 Cerebras Base is 5.2 points above that provider line, so it is a stronger result than the average Cerebras model.

Among open-weight models, the average is 55.5. Llama 3.1 Cerebras Base is 3.1 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 58.6 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 $3.36 per million input tokens, Llama 3.1 Cerebras Base is below the median input price of $4.00 across the 600 models scored on SWE-bench Verified. The models immediately around it in the ranking are shown below so you can compare score and price together.

ModelProviderContextInput / 1MAvg score
Nova Pro Mini Amazon 16384 $7.74 70.6
Claude 3.7 Sonnet Nano Anthropic 65536 $6.93 68.9
Auto Max OpenRouter 8192 $8.41 71.2
DBRX Instruct Databricks 8192 $3.21 72.4
Llama 3.1 Cerebras Base Cerebras 65536 $3.36 72.7
Arctic Instruct Snowflake 65536 $2.83 70.6
Fusion Turbo OpenRouter 8192 $8.55 71.7

Other benchmarks for Llama 3.1 Cerebras Base

BenchmarkScoreRankPercentileRelative
MMLU-Pro 77.4 265 56th
GPQA Diamond 66.9 332 45th
HumanEval 79.2 259 57th
MATH-500 74.2 342 43th
AIME 2025 67.8 298 50th
LiveCodeBench 67.7 231 62th
IFEval 82.7 253 58th
TruthfulQA 75.1 329 45th
HellaSwag 82.6 332 45th
MMMU 67.9 342 43th
Arena Elo 1387.0 259 57th

FAQ

What score does Llama 3.1 Cerebras Base get on SWE-bench Verified?

Llama 3.1 Cerebras Base scores 58.6 on SWE-bench Verified in this index. The benchmark average is 57.5 and the top score is 81.7.

How does Llama 3.1 Cerebras Base rank on SWE-bench Verified?

It ranks #347 of 600 models, in the 42nd percentile. The leader is GPT-5.2 Pro at 81.7.

Is Llama 3.1 Cerebras Base good at SWE-bench Verified?

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 SWE-bench Verified score calculated?

SWE-bench Verified is a coding 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 Llama 3.1 Cerebras Base cost?

Llama 3.1 Cerebras Base costs $3.36 per million input tokens and $15.59 per million output tokens.

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