GPT-3.5 Turbo vs Mistral Nemo

Performance benchmarks + pricing comparison — updated April 2026

GPT-3.5 Turbo

OpenAI

Budget model for simple tasks. Being phased out but still widely used.

Input$0.500/M
Output$1.50/M
Context16K tokens
Best ForSimple chatbots, basic text generation
Benchmark40/100

Mistral Nemo

Mistral

Compact 12B open-weight model co-developed with NVIDIA. Excellent coding performance at minimal cost.

Input$0.150/M
Output$0.150/M
Context128K tokens
Best ForSelf-hosted deployments, cost-sensitive coding, edge deployments
Benchmark48/100

Benchmark Performance Comparison

Third-party benchmark scores — higher is better. Data sourced from SWE-bench, LiveCodeBench, HumanEval, and BigCodeBench.

BenchmarkGPT-3.5 TurboMistral NemoLeader
Overall Score 40 48 Mistral Nemo leads by 8pts
SWE-bench Verified 32 40 Mistral Nemo leads by 8pts
LiveCodeBench 42 50 Mistral Nemo leads by 8pts
HumanEval 62 70 Mistral Nemo leads by 8pts
BigCodeBench 26 32 Mistral Nemo leads by 6pts

Cost Comparison by Scenario

Estimated cost per project with 30% cache hit rate. Actual costs may vary based on usage patterns.

ScenarioGPT-3.5 TurboMistral NemoSavings
Small Script (1K lines) $0.06 <$0.01 Mistral Nemo saves $0.05 (84%)
Medium Feature (10K lines) $0.48 $0.08 Mistral Nemo saves $0.39 (83%)
Large Project (50K lines) $2.38 $0.41 Mistral Nemo saves $1.96 (83%)
Code Review (5K lines) $0.13 $0.03 Mistral Nemo saves $0.10 (76%)

Value Analysis (Price per Benchmark Score Point)

Lower is better — how much you pay for each point of benchmark performance.

ModelOverall ScorePrice per Score PointVerdict
GPT-3.5 Turbo 40 $0.013/pt Higher cost per point
Mistral Nemo 48 $0.002/pt Better value

Mistral Nemo delivers the best value at $0.002 per score point.

Strengths & Weaknesses

GPT-3.5 Turbo

  • + Ultra-cheap
  • + Very fast
  • - Basic coding only

Mistral Nemo

  • + Open weight
  • + Self-hostable
  • - Basic coding ability

Verdict

Mistral Nemo wins on both price and performance — $0.150/M input with a benchmark score of 48/100.

For most developers, this is the clear choice between these two models.

Compare with Other Models