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// alternatives · October 2026

Llama 3.1 70B Instruct alternatives

Cheaper models that come close, budget substitutes, and the cheapest step up — chosen on published LiveBench scores and live list price, never on our opinion. Every model here supports tool calling, as Llama 3.1 70B Instruct does.

LiveBench hasn't published a run for Llama 3.1 70B Instruct. The strongest benchmarked model at a similar or lower price is Claude Haiku 5.5, scoring 69.8 overall.

Llama 3.1 70B Instruct: no published LiveBench run, $0.400 per 1M blended tokens, about $344.00/mo for a RAG assistant.

Benchmarked models at or below its price

Llama 3.1 70B Instruct has no published LiveBench run, so these are the highest-scoring benchmarked models priced no more than 25% above it — a known quantity to test against.

ModelOverallvs Llama 3.1 70B InstructBlended / 1MRAG assistantContext
Claude Haiku 5.5anthropic

50% cheaper. Head to head →

69.8—$0.200−50%$74.00/mo1M
MiniMax M3.1 Flashminimax

34% cheaper. Head to head →

66.9—$0.262−34%$102.00/mo1.0M
GPT-6 Lunaopenai

50% cheaper. Head to head →

64.6—$0.200−50%$74.00/mo1.1M
GLM 5.3 Flashz-ai

87% cheaper. Head to head →

62.1—$0.053−87%$34.59/mo1.0M
Qwen3.8 27Bqwen

15% cheaper. Head to head →

58.4—$0.342−15%$92.16/mo1M
Nemotron 3.5 Super VLnvidia

41% cheaper. Head to head →

50.2—$0.237−41%$98.00/mo1.0M

Llama 3.1 70B Instruct alternatives FAQ

What is the best alternative to Llama 3.1 70B Instruct?

Claude Haiku 5.5. 50% cheaper. Every suggestion supports tool calling, like Llama 3.1 70B Instruct.

How alternatives are chosen

  • Scores — LiveBench release 2026-10-25. Only models with a published run are suggested on quality; a missing model means “not evaluated”, not “worse”.
  • Prices — live list prices from OpenRouter, blended 3:1 input:output. Monthly figures price a RAG assistant with the published cached-input rate where there is one.
  • Same job — suggestions must support every capability Llama 3.1 70B Instruct has among tool calling and image input. Other listings of the same model (free or batch tiers) are variants, not alternatives, and are left out.

A few points on a public benchmark can hide large differences on your own tasks. Shortlist here, then decide with an eval — how to build one.