Inference Labs › Compare models › Amazon Nova Pro vs Claude Sonnet 4.5
Amazon Nova Pro vs Claude Sonnet 4.5
Side-by-side comparison of Amazon Nova Pro and Claude Sonnet 4.5: per-token pricing, context windows, strengths, and which to pick for production workloads.
Amazon Nova Pro
Strengths
- Tight integration with AWS data services.
- Strong multimodal at mid-tier pricing.
- Predictable Bedrock quotas under enterprise contracts.
Trade-offs
- Smaller community knowledge base than OpenAI/Anthropic peers.
- Tool-calling format less mature.
Claude Sonnet 4.5
Strengths
- Best-in-class on long-context recall and instruction-following.
- Detailed tool-use traces for agentic workflows.
- Strong safety profile out of the box.
Trade-offs
- Output token price is the highest in the balanced tier.
- Throughput caps tighter than OpenAI peers on most accounts.
Side-by-side pricing
| Metric | Amazon Nova Pro | Claude Sonnet 4.5 |
|---|---|---|
| Input price ($/1M tokens) | $0.80 | $3.00 |
| Output price ($/1M tokens) | $3.20 | $15.00 |
| Context window | 300K tokens | 200K tokens |
| Cost for 1M in + 1M out | $4.00 | $18.00 |
| Tier | balanced | premium |
Which should you pick?
Amazon Nova Pro is cheaper per 1M input tokens; Amazon Nova Pro is cheaper on output. For high-output workloads (long generation, structured extraction), the output rate dominates.
For long-context use cases, Amazon Nova Pro has the larger window (300K vs 200K).
In practice, the right answer depends on your traffic mix. Inference Labs lets you route the same request to whichever of these two is best for that prompt -- using policy you define (quality-first, cost-first, latency-first) without changing your application code.
Route between them automatically
Inference Labs is a vendor-neutral router that sits in front of Amazon Nova Pro, Claude Sonnet 4.5, and the other major cloud LLMs. Set per-request policy (max cost, max latency, required quality tier) and the router picks the best model per call. You keep your existing provider accounts -- we just orchestrate.
- Allowlist only the models your team has approved.
- Automatic failover if one provider is degraded.
- Semantic + exact-hash cache reduces redundant calls.
- Per-workspace spend caps and audit-ready trace logs.
Stop hard-coding model names. Start a free Inference Labs trial → -- 500 credits, no card required, see your routing decisions in the dashboard within minutes.