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Grok 4.3 vs Cohere Command R (08-2024): Which AI Model Should You Choose?

Pricing, context windows, latency, capabilities, and a one-line code switch — everything you need to pick the right model.

xAI
Multimodal
vs
xAI
Text & Chat
Verdict

Choose Grok 4.3 for cost-sensitive workloads — it is roughly 150.0× cheaper on input tokens. Choose Cohere Command R (08-2024) when you need its broader capabilities or stronger benchmarks.

Choose Grok 4.3 for long documents (1.0M tokens context). Choose Cohere Command R (08-2024) for shorter prompts where the smaller window keeps latency and cost down.

These models serve different use cases (Multimodal vs Text & Chat) — pick the one whose category matches your workload.

Side-by-side specs

SpecGrok 4.3Cohere Command R (08-2024)
ProviderxAIxAI
CategoryMultimodalText & Chat
Input cost / 1M tokens€0.0010€0.150
Output cost / 1M tokens€0.0030€0.600
Context window1.0M tokens128K tokens
Max output tokens1,000,0004,096
Avg. latency——
FeaturedYes—
NewYes—
Capabilities
text
image
text

Pricing example

A typical chat workload of 100,000 input tokens plus 50,000 output tokens.

Grok 4.3
€0.0003

100K in × €0.0010 + 50K out × €0.0030

Cohere Command R (08-2024)
€0.0450

100K in × €0.150 + 50K out × €0.600

For this workload, Grok 4.3 is cheaper than Cohere Command R (08-2024) by €0.0447 per request.

Switch in one line

Both models live behind Railwail's OpenAI-compatible endpoint. Replace the model string and you are done.

JavaScript / TypeScript
import OpenAI from "openai";

const client = new OpenAI({
  apiKey: process.env.RAILWAIL_API_KEY,
  baseURL: "https://railwail.com/v1",
});

// Before — using Grok 4.3
let r = await client.chat.completions.create({
  model: "grok-4.3",
  messages: [{ role: "user", content: "Hello" }],
});

// After — switched to Cohere Command R (08-2024)
r = await client.chat.completions.create({
  model: "command-r-08-2024",
  messages: [{ role: "user", content: "Hello" }],
});
Python
from openai import OpenAI

client = OpenAI(
    api_key=os.environ["RAILWAIL_API_KEY"],
    base_url="https://railwail.com/v1",
)

# Before — using Grok 4.3
r = client.chat.completions.create(
    model="grok-4.3",
    messages=[{"role": "user", "content": "Hello"}],
)

# After — switched to Cohere Command R (08-2024)
r = client.chat.completions.create(
    model="command-r-08-2024",
    messages=[{"role": "user", "content": "Hello"}],
)
cURL
# Before — using Grok 4.3
curl https://railwail.com/v1/chat/completions \
  -H "Authorization: Bearer $RAILWAIL_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "model": "grok-4.3",
    "messages": [{"role": "user", "content": "Hello"}]
  }'

# After — switched to Cohere Command R (08-2024)
curl https://railwail.com/v1/chat/completions \
  -H "Authorization: Bearer $RAILWAIL_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "model": "command-r-08-2024",
    "messages": [{"role": "user", "content": "Hello"}]
  }'

Which one wins for...

Quick verdicts derived from public specs. Always validate on your own workload.

Coding
Grok 4.3

Higher coding category match or larger context wins.

Writing
Grok 4.3

Bigger context window helps maintain long-form coherence.

Long documents
Grok 4.3

The larger context window is the deciding factor.

Vision
Grok 4.3

Multimodal/vision support is required for image inputs.

Real-time chat
Tie

Lower average latency wins for interactive UX.

Cost-sensitive
Grok 4.3

The model with the lower input-token price wins.

Frequently asked questions

Which is cheaper, Grok 4.3 or Cohere Command R (08-2024)?
Grok 4.3 is cheaper. On a 100K input + 50K output example, Grok 4.3 costs about €0.0003 versus €0.0450 for Cohere Command R (08-2024) — a saving of €0.0447.
Which has more context, Grok 4.3 or Cohere Command R (08-2024)?
Grok 4.3 has the larger context window at 1.0M tokens, compared to 128K tokens for Cohere Command R (08-2024).
Is Grok 4.3 better than Cohere Command R (08-2024) for coding?
For coding-heavy workloads we lean toward Grok 4.3 on this comparison — it scores higher on the relevant heuristics (category, tags, or context window). Both models are usable for code via Railwail's OpenAI-compatible endpoint, so the safest path is to A/B test on your own prompts.
Can I use both Grok 4.3 and Cohere Command R (08-2024) via Railwail?
Yes. Both Grok 4.3 and Cohere Command R (08-2024) are accessible through a single Railwail API key and the OpenAI-compatible /v1/chat/completions endpoint. You only change the "model" parameter to switch between them — no SDK swap, no separate billing.
How do I switch from Grok 4.3 to Cohere Command R (08-2024)?
Replace the model identifier "grok-4.3" with "command-r-08-2024" in your request payload. Everything else — API key, base URL, request shape — stays the same. See the code example on this page for the exact one-line change.

Try Grok 4.3 and Cohere Command R (08-2024) side by side

One API key, one endpoint, both models. Start free — no credit card required.

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