Cohere Embed v4 vs MythoMax 13B

Compare Cohere Embed v4 and MythoMax 13B: pricing, performance, context window, latency, and best use cases. Side-by-side comparison on XALEN.

Updated 2026-05-21 · By Abhishek Raj · Our methodology

All Cohere models All Gryphe models What is an LLM API? Python Quickstart What is inference?
Feature Cohere Embed v4 MythoMax 13B
CategoryEmbeddingOpen Source
Parameters~400M13B
Context Window128K4K
Input Price$0.001/1M tokens$0.01/1M tokens
Output PriceN/A/1M tokens$0.02/1M tokens
Latency~15ms~100ms

Choose Cohere Embed v4 when:

  • ✓ Long document RAG
  • ✓ Multimodal search
  • ✓ Large knowledge bases
Key Strengths:

128K context, Multimodal embedding, Matryoshka

Choose MythoMax 13B when:

  • ✓ Story generation
  • ✓ Creative content
  • ✓ Interactive fiction
Key Strengths:

Creative writing, Roleplay, Narrative quality

Verdict: Cohere Embed v4 vs MythoMax 13B

For cost efficiency, Cohere Embed v4 wins at $0.001/1M input tokens. For speed, MythoMax 13B is faster at ~100ms. Cohere Embed v4 excels at Long document RAG while MythoMax 13B is better for Story generation. Both are available on XALEN through a single API — try them in the Playground to see which fits your workload.

Detailed Analysis

Pricing Comparison

Cohere Embed v4 costs $0.001/1M input tokens and N/A/1M output tokens. MythoMax 13B costs $0.01 input and $0.02 output. Cohere Embed v4 is 10.0x cheaper on input tokens. XALEN offers batch processing at 50% discount on both models.

Performance & Context

Cohere Embed v4 has a 128K context window with ~15ms latency. MythoMax 13B offers 4K context at ~100ms. Cohere Embed v4 has the larger context window.

Best For

Cohere Embed v4 (Embedding) is optimized for: Long document RAG, Multimodal search, Large knowledge bases. MythoMax 13B (Open Source) works best for: Story generation, Creative content, Interactive fiction.

Try Both on XALEN

Both models are available through XALEN's OpenAI-compatible API. Switch between them by changing the model parameter:

from xalen import XALEN

client = XALEN(api_key="xln_test_YOUR_KEY")

# Use Cohere Embed v4
response_a = client.chat.completions.create(
    model="embed-v4",
    messages=[{"role": "user", "content": "Your question here"}]
)

# Use MythoMax 13B
response_b = client.chat.completions.create(
    model="mythomax-13b",
    messages=[{"role": "user", "content": "Your question here"}]
)

Start Building with XALEN

200+ AI models. One API. Pay-as-you-go.

Get API Key Try in Playground

Frequently Asked Questions

Which is better, Cohere Embed v4 or MythoMax 13B?

Cohere Embed v4 (Embedding, ~400M) offers 128K context. MythoMax 13B (Open Source, 13B) offers Creative writing. Choose Cohere Embed v4 for Long document RAG or MythoMax 13B for Story generation.

How much does Cohere Embed v4 cost vs MythoMax 13B?

Cohere Embed v4: $0.001/1M input, N/A/1M output. MythoMax 13B: $0.01/1M input, $0.02/1M output. Both available on XALEN with batch processing at 50% discount.

Can I use both models on XALEN?

Yes. XALEN provides 200+ models through a single OpenAI-compatible API. Switch between Cohere Embed v4 and MythoMax 13B by changing the model parameter. No code changes needed.

Related Comparisons

Cohere Embed v4 vs Text Embedding 3 Large Cohere Embed v4 vs Gemma 3 27B Cohere Embed v4 vs Llama 4 Scout Cohere Embed v4 vs Llama 4 Maverick Cohere Embed v4 vs Llama 3.3 70B Cohere Embed v4 vs Llama 3.1 405B

Last updated: 2026-05-21. Pricing and specifications may change. Check pricing page for latest rates.