Assessment 2 — Model Comparison Analysis

1. Models Evaluated

ModelProviderContext Window
Claude Sonnet 4.6Anthropic (via Bedrock)1M tokens
Claude Opus 4.6Anthropic (via Bedrock)1M tokens
GPT-OSS 20BOpenAI (via Bedrock)128K tokens
GLM 5Zhipu AI (via Bedrock)200K tokens

2. Performance Characteristics

Latency (averaged over 3 runs)

ModelAvg TTFTAvg TotalNotes
Claude Sonnet 4.6~1248ms~4.59sConsistent, balanced output
Claude Opus 4.6~1575ms~4.30sSlower TTFT, similar total
GPT-OSS 20B~452ms~1.16s3x faster TTFT
GLM 5~1415ms~2.54sVariable TTFT, shorter responses

Cost

ModelInput / 1K tokensOutput / 1K tokensEst. per request
Claude Sonnet 4.6$0.003$0.015$0.0060
Claude Opus 4.6$0.015$0.075$0.0300
GPT-OSS 20B$0.00015$0.0002$0.000135
GLM 5$0.0005$0.002$0.00085

Opus is 5x the cost of Sonnet and ~220x the cost of GPT-OSS 20B per request.

3. Quality Evaluation (LLM-as-Judge)

8 test cases across reasoning, factual recall, code generation, summarization, instruction following, creative writing, and safety. Claude Opus 4.6 served as the judge, scoring accuracy, relevance, and coherence (1-5).

→ Run the interactive evaluation dashboard

4. Use Case Recommendations

Use CaseModelRationale
Quick Q&A / chatClaude Sonnet 4.6Best balance of quality and cost at $0.006/req
Complex reasoningClaude Opus 4.6Highest quality, similar total latency despite higher TTFT
High-volume / cost-sensitiveGPT-OSS 20B~220x cheaper, 3x faster TTFT
Multilingual / CJKGLM 5Purpose-built for CJK, mid-range cost

5. Trade-offs Observed

Quality vs. Speed

GPT-OSS 20B was the fastest model (~452ms TTFT vs ~1200-1600ms for others) but produced more verbose and occasionally less focused responses. Opus and Sonnet had similar total response times despite Opus having a higher TTFT, suggesting Opus generates tokens faster once started.

Quality vs. Cost

The quality gap between Sonnet and Opus was smaller than the 5x cost difference suggests. For most conversational use cases, Sonnet delivers comparable quality at a fraction of the cost. Opus justifies its premium only for complex multi-step reasoning or analysis tasks.

Consistency

Sonnet and Opus were highly consistent across repeated runs (TTFT variance <300ms). GPT-OSS 20B showed more variance in output length (191-467 tokens for the same prompt). GLM 5 had the widest TTFT variance (758ms-1999ms), suggesting less predictable cold-start behavior.

6. Conclusion

For a production GenAI chat application, Claude Sonnet 4.6 offers the best overall value — strong quality at reasonable cost ($0.006/request) and acceptable latency. Opus should be reserved for high-stakes reasoning tasks where accuracy is critical and the 5x cost premium is justified. GPT-OSS 20B is ideal for cost-sensitive, high-volume workloads where sub-second TTFT matters more than output refinement.