LLM Comparison
Claude Haiku 5.5 vs Command R (08-2024)
Side-by-side specs, pricing & capabilities
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2/6 modelsSame tier:
| Organization | ||
| OpenTools Score | ||
| Family | Claude | Command |
| Status | Current | Current |
| Release Date | Oct 2026 | Aug 2024 |
| Context Window | 1.0M tokens | 128K tokens |
| Input Price | $0.10/M tokens | $0.15/M tokens |
| Output Price | $0.50/M tokens | $0.60/M tokens |
| Pricing Notes | Anthropic Claude API global standard tier, USD per million tokens. Prompts up to 100,000 tokens: $0.10 input, $0.50 output, $0.125 five-minute cache write, $0.20 one-hour cache write, and $0.01 cache read. Prompts above 100,000 tokens: $0.50 input, $2.50 output, $0.625 five-minute cache write, $1 one-hour cache write, and $0.05 cache read. Batch API requests receive a 50% discount. US-only data residency applies a 1.1x token-price multiplier. The Batch API beta supports up to 300,000 output tokens; 128,000 is the standard API cap recorded here. | — |
| Capabilities | reasoningvisiontool-uselong-contextcontext-caching | textcode |
| Max Output | 128K tokens | 4K tokens |
| API Identifier | claude-haiku-5-5 | cohere/command-r-08-2024 |
| Benchmarks | ||
| Artificial Analysis Intelligence Index v4.3.2 | 43.4 indexartificial-analysis | — |
| View Claude Haiku 5.5 | View Command R (08-2024) | |
Cost Calculator
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| Model | Input | Output | Total / mo | vs Best |
|---|---|---|---|---|
| Claude Haiku 5.5Cheapest | $0.10 | $0.25 | $0.35 | — |
| Command R (08-2024) | $0.15 | $0.30 | $0.45 | +29% |
Anthropic
Claude Haiku 5.5
Claude Haiku 5.5 is Anthropic's fast proprietary model for high-volume classification, extraction, routing, and subagent workloads. It accepts text and images, returns text, uses adaptive thinking, and supports a 1,000,000-token context window with up to 128,000 output tokens on standard API calls.
Cohere
Command R (08-2024)
Command R (08-2024) is a large language model from Cohere. Supports up to 128,000 token context window. Achieves 68.4% on MMLU. Available from $0.15/M input tokens.
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