Cheaper alternatives to Phi 4

Microsoft LMArena 1216.8 $0.087/M on a balanced workload prices as of 2026-08-28

12 models are both better and cheaper, giving up nothing.

Of the 133 models carrying both an independent score and a published price at the same delivery mode, 12 score at least as high as Phi 4 and cost no more under at least one workload. 12 match or beat it on every capability we hold — context, maximum output, input modes, tool use and extended reasoning.

Dominance is not a property of a model. It is a property of a model, a capability lens and a workload, and all three are named on every row. Scores are LMArena Elo, used under CC BY 4.0 from the official dataset; prices are blended per million tokens. A higher score is not a drop-in replacement.

This page is built from that comparison and nothing else. When no model is both better and cheaper than Phi 4, it is not generated.

Where it holds

Workload	Phi 4 $/M	Better and cheaper
Balanced	$0.087	8
Summarise	$0.073	11
Chat	$0.098	8
Code gen	$0.112	6
Agentic	$0.081	11

Workload mixes are defined on the methodology page. Cached input is priced at the cached rate, and reasoning tokens at the worse of the reasoning and output rates.

What you would be replacing

Intelligence	1216.8
Context window	16K
Max output	15K
Input modes	text
Tool use	no
Extended reasoning	no

A replacement has to clear every line above, not just the score. Full record for Phi 4.

Better and cheaper, nothing given up 12

Each of these matches or beats Phi 4 on context, maximum output, input modes, tool use and reasoning, scores at least as high, and costs no more.

#	Model	Intelligence	$/M	Holds under
1	Qwen3 30B A3B Instruct 2507 Qwen	1384.3 +167.5	$0.084	Balanced −4% Summarise −25% Agentic −13%
2	Solar Pro 4 Upstage	1376.2 +159.4	$0.052	Balanced −40% Summarise −62% Chat −40% Code gen −27% Agentic −64%
3	gpt-oss-120b OpenAI	1365.6 +148.8	$0.070	Balanced −20% Summarise −41% Chat −8% Agentic −29%
4	Gemma 3 12B Google	1334.2 +117.4	$0.075	Balanced −14% Summarise −25% Chat −8% Code gen −2% Agentic −19%
5	Granite 4.1 8B IBM	1291.6 +74.8	$0.063	Balanced −29% Summarise −29% Chat −29% Code gen −29% Agentic −29%
6	Gemma 3 4B Google	1290.8 +74	$0.063	Balanced −29% Summarise −29% Chat −29% Code gen −29% Agentic −29%
7	gpt-oss-20b OpenAI	1287.8 +71	$0.055	Balanced −37% Summarise −52% Chat −29% Code gen −20% Agentic −44%
8	Mistral Small 3 Mistral	1233.6 +16.8	$0.058	Balanced −34% Summarise −30% Chat −37% Code gen −39% Agentic −32%
9	DeepSeek V4 Flash 0423 DeepSeek	1431.6 +214.8	$0.067 summarise	Summarise −9% Chat −4% Agentic −32%
10	MiMo-V2.5 Xiaomi	1427.3 +210.5	$0.079 agentic	Agentic −1%
11	GLM 4.7 Flash Z.ai	1352.9 +136.1	$0.063 summarise	Summarise −15%
12	GPT-5 Nano OpenAI	1320.3 +103.5	$0.055 summarise	Summarise −26% Agentic −6%

What this compares, and what it leaves out

Quality is LMArena Elo, used under CC BY 4.0 from the official dataset. The 95% confidence interval on a difference between two scores is about ±10.68 points, so a gap smaller than that is marked tie rather than an improvement — see significance bands.
188 further models at this delivery mode carry a price but no independent score. They are absent from the comparison in both directions — unrated is not a zero, and an unmeasured model is neither an alternative nor a worse buy.
Retired models are never offered as an alternative, and a model only competes against its own delivery mode: batch trades latency for price, so it is not a like-for-like swap.
Nothing here measures latency, throughput, rate limits or how a model behaves on your prompts. Two models with the same index score are not interchangeable.
The models that nothing beats on both axes are on the value frontier, and every other model something cheaper beats is listed here.