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// alternatives · October 2026

GPT-5.2-Codex 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 and image input, as GPT-5.2-Codex does.

LiveBench hasn't published a run for GPT-5.2-Codex. The strongest benchmarked model at a similar or lower price is GPT-6.1 Sol, scoring 84.1 overall.

GPT-5.2-Codex: no published LiveBench run, $4.81 per 1M blended tokens, about $1,610/mo for a RAG assistant.

Benchmarked models at or below its price

GPT-5.2-Codex 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 GPT-5.2-CodexBlended / 1MRAG assistantContext
GPT-6.1 Solopenai

17% cheaper. Head to head →

84.1—$4.00−17%$1,440/mo1.1M
Claude Sonnet 5.5anthropic

17% cheaper. Head to head →

80.0—$4.00−17%$1,440/mo1M
Gemini 4 Argongoogle

17% cheaper. Head to head →

79.3—$4.00−17%$1,440/mo1.0M
GPT-6.1 Terraopenai

58% cheaper. Head to head →

77.8—$2.00−58%$720.00/mo1.1M
DeepSeek V4.1 Flash 1017deepseek

89% cheaper. Head to head →

74.0—$0.525−89%$194.40/mo1.0M
Kimi K3.1 Promoonshotai

17% cheaper. Head to head →

71.3—$4.00−17%$1,480/mo1.0M

GPT-5.2-Codex alternatives FAQ

What is the best alternative to GPT-5.2-Codex?

GPT-6.1 Sol. 17% cheaper. Every suggestion supports tool calling and image input, like GPT-5.2-Codex.

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 GPT-5.2-Codex 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.