Mistral Small 3.1 vs BGE Large v1.5
Compare Mistral Small 3.1 and BGE Large v1.5: pricing, performance, context window, latency, and best use cases. Side-by-side comparison on XALEN.
Updated 2026-05-21 · By Abhishek Raj · Our methodology
| Feature | Mistral Small 3.1 | BGE Large v1.5 |
|---|---|---|
| Category | Compact | Embedding |
| Parameters | 24B | 326M |
| Context Window | 128K | 512 |
| Input Price | $0.02/1M tokens | $0.001/1M tokens |
| Output Price | $0.04/1M tokens | N/A/1M tokens |
| Latency | ~120ms | ~15ms |
Choose Mistral Small 3.1 when:
- ✓ Lightweight tasks
- ✓ Classification
- ✓ Simple generation
128K context, Low cost, Fast
Choose BGE Large v1.5 when:
- ✓ Budget RAG
- ✓ Knowledge bases
- ✓ Document clustering
Very low cost, Good multilingual, Fast
Verdict: Mistral Small 3.1 vs BGE Large v1.5
For cost efficiency, BGE Large v1.5 wins at $0.001/1M input tokens. For speed, Mistral Small 3.1 is faster at ~120ms. Mistral Small 3.1 excels at Lightweight tasks while BGE Large v1.5 is better for Budget RAG. Both are available on XALEN through a single API — try them in the Playground to see which fits your workload.
Detailed Analysis
Pricing Comparison
Mistral Small 3.1 costs $0.02/1M input tokens and $0.04/1M output tokens. BGE Large v1.5 costs $0.001 input and N/A output. BGE Large v1.5 is 20.0x cheaper on input tokens. XALEN offers batch processing at 50% discount on both models.
Performance & Context
Mistral Small 3.1 has a 128K context window with ~120ms latency. BGE Large v1.5 offers 512 context at ~15ms. Mistral Small 3.1 has the larger context window.
Best For
Mistral Small 3.1 (Compact) is optimized for: Lightweight tasks, Classification, Simple generation. BGE Large v1.5 (Embedding) works best for: Budget RAG, Knowledge bases, Document clustering.
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 Mistral Small 3.1
response_a = client.chat.completions.create(
model="mistral-small-3-1",
messages=[{"role": "user", "content": "Your question here"}]
)
# Use BGE Large v1.5
response_b = client.chat.completions.create(
model="bge-large-v1-5",
messages=[{"role": "user", "content": "Your question here"}]
)
Frequently Asked Questions
Which is better, Mistral Small 3.1 or BGE Large v1.5?
Mistral Small 3.1 (Compact, 24B) offers 128K context. BGE Large v1.5 (Embedding, 326M) offers Very low cost. Choose Mistral Small 3.1 for Lightweight tasks or BGE Large v1.5 for Budget RAG.
How much does Mistral Small 3.1 cost vs BGE Large v1.5?
Mistral Small 3.1: $0.02/1M input, $0.04/1M output. BGE Large v1.5: $0.001/1M input, N/A/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 Mistral Small 3.1 and BGE Large v1.5 by changing the model parameter. No code changes needed.
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Last updated: 2026-05-21. Pricing and specifications may change. Check pricing page for latest rates.