Cheaper alternatives to Trinity Large Thinking

Arcee LMArena 1341.9 $0.378/M on a balanced workload prices as of 2026-08-28

1 model is 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, 21 score at least as high as Trinity Large Thinking and cost no more under at least one workload. 1 matches or beats it on every capability we hold — context, maximum output, input modes, tool use and extended reasoning. 20 do not, and every row names what it drops.

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 Trinity Large Thinking, it is not generated.

Where it holds

Workload	Trinity Large Thinking $/M	Better and cheaper	With a trade
Balanced	$0.378	1	17
Summarise	$0.206	1	17
Chat	$0.424	1	16
Code gen	$0.585	1	16
Agentic	$0.219	1	15

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	1341.9
Context window	262K
Max output	236K
Input modes	text
Tool use	yes
Extended reasoning	yes

A replacement has to clear every line above, not just the score. Full record for Trinity Large Thinking.

Better and cheaper, nothing given up 1

Each of these matches or beats Trinity Large Thinking 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	DeepSeek V4 Flash 0423 DeepSeek	1431.6 +89.7	$0.101	Balanced −73% Summarise −68% Chat −78% Code gen −79% Agentic −75%

Cheaper and higher-scoring, but you give something up 20

These score at least as high and cost no more on the two plotted axes, and lose something that is not on them. Read the last column before switching.

Model	Intelligence	$/M	Holds under	What you give up
Gemma 4 31B Google	1441.7 +99.8	$0.152	Balanced −60% Summarise −56% Chat −58% Code gen −60% Agentic −53%	236K → 16K max output
Hy3 Tencent	1441.2 +99.3	$0.144	Balanced −62% Summarise −63% Chat −62% Code gen −61% Agentic −62%	236K → 128K max output
Gemma 4 26B A4B Google	1434.6 +92.7	$0.138	Balanced −64% Summarise −59% Chat −58% Code gen −60% Agentic −50%	236K → 16K max output
MiMo-V2.5 Xiaomi	1427.3 +85.4	$0.175	Balanced −54% Summarise −48% Chat −63% Code gen −64% Agentic −64%	236K → 131K max output
DeepSeek V3.2 DeepSeek	1424.6 +82.7	$0.290	Balanced −23% Chat −37% Code gen −45% Agentic −9%	262K → 164K context 236K → 147K max output
DeepSeek V3.2 Exp DeepSeek	1424.4 +82.5	$0.305	Balanced −19% Chat −23% Code gen −40%	262K → 164K context 236K → 66K max output
Qwen3 235B A22B Instruct 2507 Qwen	1419.3 +77.4	$0.205	Balanced −46% Summarise −45% Chat −35% Code gen −37% Agentic −27%	236K → 16K max output no extended reasoning
Qwen3 Next 80B A3B Instruct Qwen	1418.6 +76.7	$0.350	Balanced −7% Summarise −31%	no extended reasoning
Step 3.5 Flash StepFun	1403.8 +61.9	$0.150	Balanced −60% Summarise −47% Chat −58% Code gen −62% Agentic −41%	236K → 66K max output
Qwen3.5-Flash Qwen	1397.6 +55.7	$0.114	Balanced −70% Summarise −64% Chat −66% Code gen −69% Agentic −57%	236K → 66K max output
Qwen3 30B A3B Instruct 2507 Qwen	1384.3 +42.4	$0.084	Balanced −78% Summarise −73% Chat −75% Code gen −77% Agentic −68%	236K → 32K max output no extended reasoning
Solar Pro 4 Upstage	1376.2 +34.3	$0.052	Balanced −86% Summarise −87% Chat −86% Code gen −86% Agentic −87%	236K → 131K max output
GLM 4.5 Air Z.ai	1382.8 +40.9	$0.310	Balanced −18% Summarise −34% Chat −9% Code gen −5% Agentic −20%	262K → 131K context 236K → 98K max output
gpt-oss-120b OpenAI	1365.6 +23.7	$0.070	Balanced −81% Summarise −79% Chat −79% Code gen −80% Agentic −74%	262K → 131K context 236K → 118K max output
Gemma 3 27B Google	1358.3 +16.4	$0.172	Balanced −54% Summarise −58% Chat −49% Code gen −49% Agentic −49%	236K → 118K max output no extended reasoning
GLM 4.7 Flash Z.ai	1352.9 +11	$0.145	Balanced −62% Summarise −69% Chat −57% Code gen −56% Agentic −63%	262K → 203K context 236K → 16K max output
Mercury 2 Inception	1357.8 +15.9	$0.375	Balanced −1% Chat −10% Code gen −9% Agentic −13%	262K → 128K context 236K → 50K max output
GPT-5.6 Luna OpenAI	1428.5 +86.6	$0.199 summarise	Summarise −3%	236K → 128K max output
GPT-5.4 Nano OpenAI	1372.8 +30.9	$0.201 summarise	Summarise −2%	236K → 128K max output
Qwen3 Next 80B A3B Thinking Qwen	1367.5 +25.6	$0.203 summarise	Summarise −2%	236K → 33K max output

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.