Choose Cohere: Command R (08-2024) if…
- you need tool / function calling — to call your APIs and run agent loops; Inference.net: Schematron V2 Small does not advertise it
Neither wins outright: Cohere: Command R (08-2024) is the pick when you need tool / function calling, Inference.net: Schematron V2 Small when cost matters at scale.
| Spec | Cohere: Command R (08-2024) | Inference.net: Schematron V2 Small |
|---|---|---|
| Provider | Cohere | Inference.net |
| Input price (per 1M tokens) | $0.15 | $0.05 |
| Output price (per 1M tokens) | $0.60 | $0.23 |
| Blended price (3:1 input/output) | $0.26 | $0.10 |
| Cheaper than … of all models we track | 65% | 82% |
| Context window | 128K tokens (~192 pages) | 128K tokens (~192 pages) |
| Larger context than … of all models | 14% | 14% |
| Max output per response | 4K tokens (~3,000 words) | 4K tokens (~3,100 words) |
| Input types | text | text |
| Output types | text | text |
| Free variant | No | No |
| Listed since | 2024-08-30 | 2026-09-12 |
Monthly cost at list price for five common workloads. Token counts per unit are stated so you can scale them to your own traffic. A workload that does not fit a model's context window is marked rather than priced.
| Workload (per month) | Cohere: Command R (08-2024) | Inference.net: Schematron V2 Small | Difference |
|---|---|---|---|
| Customer-support chatbot 50,000 conversations — each a 6-turn conversation (1,500 in / 400 out tokens) | $23.25 | $8.35 | Inference.net: Schematron V2 Small saves $14.90 |
| RAG search over documents 20,000 questions — each a question answered from ~8 retrieved passages (6,000 in / 500 out tokens) | $24.00 | $8.30 | Inference.net: Schematron V2 Small saves $15.70 |
| Coding / tool-using agent 2,000 tasks — each a multi-step task with tool calls and file context (60,000 in / 6,000 out tokens) | $25.20 | $8.76 | Inference.net: Schematron V2 Small saves $16.44 |
| Batch summarisation 10,000 documents — each a 6,000-word report summarised to a page (8,000 in / 600 out tokens) | $15.60 | $5.38 | Inference.net: Schematron V2 Small saves $10.22 |
| Long-document analysis 500 documents — each a 150-page contract or codebase read in one pass (100,000 in / 2,000 out tokens) | $8.10 | $2.73 | Inference.net: Schematron V2 Small saves $5.37 |
| Capability | Cohere: Command R (08-2024) | Inference.net: Schematron V2 Small | What it lets you do |
|---|---|---|---|
| Tool / function calling | ✓ Yes | — | call your APIs and run agent loops |
| Structured output (JSON schema) | ✓ Yes | ✓ Yes | return JSON that validates against your schema |
| Reasoning / thinking mode | — | — | spend extra tokens thinking before answering hard problems |
| Image input | — | — | read screenshots, charts and scanned pages |
| Audio input | — | — | take speech or audio directly |
| File / PDF input | — | — | accept documents without your own parsing step |
| Image output | — | — | generate images, not just text |
| Built-in web search | — | — | answer from live web results |
| Seed (reproducible sampling) | ✓ Yes | ✓ Yes | repeat a generation for tests and evals |
| Log-probabilities | — | — | read token confidence for classification and scoring |
From each model's published parameters and input/output types. “—” means not advertised, not proven absent.
Neither wins outright: Cohere: Command R (08-2024) is the pick when you need tool / function calling, Inference.net: Schematron V2 Small when cost matters at scale. In short: Cohere: Command R (08-2024) when you need tool / function calling; Inference.net: Schematron V2 Small when cost matters at scale, you want the newer model.
Inference.net: Schematron V2 Small is cheaper: $0.10 vs $0.26 per 1M tokens at a typical 3:1 input/output mix, 64% less. For 50,000 support conversations a month that is $8.35 against $23.25.
Cohere: Command R (08-2024) costs $0.15 per 1M input tokens and $0.60 per 1M output tokens; Inference.net: Schematron V2 Small costs $0.05 input and $0.23 output. Output tokens are billed separately, so long answers shift the gap.
Both take 128K tokens per request — roughly 192 pages of text.
Tool calling — Cohere: Command R (08-2024): yes, Inference.net: Schematron V2 Small: not advertised. JSON-schema structured output — Cohere: Command R (08-2024): yes, Inference.net: Schematron V2 Small: yes.
Neither accepts image input — both are text-in models.
No free variant is listed for either; both are pay-per-token.
Cohere: Command R (08-2024) can write up to 4K tokens (about 3,000 words) per response; Inference.net: Schematron V2 Small up to 4K (about 3,100 words).
Cohere: Command R (08-2024) was listed on 2024-08-30; Inference.net: Schematron V2 Small on 2026-09-12.
command-r-08-2024 is an update of the [Command R](/models/cohere/command-r) with improved performance for multilingual retrieval-augmented generation (RAG) and tool use. More broadly, it is better at math, code and reasoning and...
Full Cohere: Command R (08-2024) specs →Schematron V2 Small is a 3B-parameter HTML-to-JSON extraction model from Inference.net. It prioritizes extraction quality for complex schemas and long pages. Extraction instructions must be supplied through a JSON schema...
Full Inference.net: Schematron V2 Small specs →