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Choosing between LLM providers

Written by , Founder, AskVault · Reviewed by Aashiq
Last updated: · 5 min read

The five factors

When picking a provider:

  1. Quality on your domain. Generic benchmarks rarely reflect your use case. Test.
  2. Cost per query. Per-token billing scales with usage.
  3. Latency. First-token latency plus full-response time.
  4. Compliance. SOC 2, HIPAA, GDPR commitments.
  5. Data handling. "Not used for training" guarantee.

Major providers (2026)

Without endorsing any specifically:

  • OpenAI. Broad model family, strong general performance.
  • Anthropic. Claude family, strong reasoning and safety.
  • Google. Gemini family, strong multimodal.
  • Open-source. Llama, Mistral, Qwen via self-hosting or hosting providers.

Each has trade-offs.

Quality on your domain

Generic benchmarks (MMLU, HumanEval) don't tell you how a model handles your content.

How to test:

  1. Pick 30 representative queries from your real data.
  2. Send each to 3 to 5 models.
  3. Score per relevance, accuracy, tone.

Often the differences surprise. A "weaker" model may handle your specific domain better than a "stronger" one.

Cost comparison

Per 1 million tokens (input + output combined):

  • Premium tier. $5 to $30.
  • Mid-tier. $1 to $10.
  • Open-source self-hosted. $0.10 to $2 (plus your infrastructure).

For a SaaS with 50,000 monthly queries averaging 500 tokens each:

  • Premium. $125 to $750 per month.
  • Mid-tier. $25 to $250.
  • Open-source. Self-hosted infra dominates.

Latency

  • Premium models. 500 ms to 2 seconds first-token.
  • Smaller models. 200 ms to 800 ms.
  • Self-hosted. Depends on your infrastructure.

For voice channel, lower latency matters. For email channel, less so.

Compliance commitments

Providers vary:

  • SOC 2 Type II. Most major providers have it.
  • HIPAA BAA. Available on enterprise plans for some providers.
  • GDPR compliance. Standard for serious providers.
  • Data residency (EU, US-only).** Varies.

For regulated industries: confirm compliance fits your needs.

Data handling commitments

Critical for B2B:

  • "Not used to train shared models" should be in writing.
  • Retention period of your prompts/responses.
  • Sub-processor disclosure.

Some providers offer zero-retention modes for highest sensitivity.

Multi-provider strategy

Common patterns:

Pattern 1: primary plus fallback. Premium model primary; cheaper fallback if primary errors or rate-limits.

Pattern 2: per-use-case routing. Premium for complex queries; lighter for FAQ-style.

Pattern 3: regional routing. EU customers to EU-hosted; US to US-hosted.

About 50 to 70% of mature SaaS use multi-provider.

AskVault's approach

AskVault routes through a multi-provider layer:

  • Free tier uses a fast, cost-effective model.
  • Paid tiers use higher-capability models.
  • Enterprise can bring their own model or pin a specific provider.

Configured under Model Selector.

Switching costs

Migrating between providers:

  • Prompt tuning. Each provider has prompt-style preferences.
  • Few-shot examples may need adjustment.
  • Cost re-validation.
  • Latency re-test.

About 1 to 2 weeks per provider switch for medium-complexity setup.

Common pitfalls

Picking based on benchmarks alone. Test on your real data.

Lock-in. Avoid provider-proprietary features. Stay portable.

Over-optimizing cost. A "cheap" model with 10% worse accuracy may cost more in support overhead than premium.

Ignoring data-handling fine print. Read the terms; verify "not for training".

FAQ

Should I always pick the cheapest?

For high-volume low-stakes, yes. For high-stakes (legal, medical), premium.

Will providers change pricing?

Yes regularly. Monitor; switch costs typically pay back in 6 to 12 months.

Can I switch mid-deployment?

Yes. About 1 to 2 weeks of re-testing required.

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