---
title: "Compare alternatives to Trinity Large Thinking · Undominated.ai"
canonical: https://undominated.ai/alternatives/arcee-ai__trinity-large-thinking/
description: "28 alternatives score at least as high as Trinity Large Thinking and cost no more under at least one listed workload. 11 preserve recorded capabilities; 17 have named trade-offs."
---

# Compare alternatives to Trinity Large Thinking · Undominated.ai

> 28 alternatives score at least as high as Trinity Large Thinking and cost no more under at least one listed workload. 11 preserve recorded capabilities; 17 have named trade-offs.

# Alternatives to Trinity Large Thinking

Arcee · LMArena 1340 · $0.388/M on a balanced workload · prices as of 2026-10-06

 [Compare models](https://undominated.ai/compare/) Comparison context

Choose up to three standard models in Compare.

Requirements and prompt length apply in Compare. This page keeps its stated price basis and workload controls.

## 11 models are higher-scoring or cheaper, with neither dimension worse.

Of the 144 models carrying both an independent score and a published price at the same delivery mode, **28** score at least as high as Trinity Large Thinking and cost no more under at least one listed workload, with at least one of those dimensions improved. **11** match or beat its recorded context, maximum output, input modes, tool use and extended reasoning. **17** have a recorded capability loss, named on every row.

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 only while a candidate improves score or price without worsening the other under a listed workload. When that comparison no longer holds, it is not generated.

## Where it holds

| Workload | Trinity Large Thinking $/M | Recorded capabilities preserved | Recorded capability losses |
| --- | --- | --- | --- |
| Balanced | $0.388 | 8 | 16 |
| Summarise | $0.223 | 11 | 15 |
| Chat | $0.413 | 8 | 14 |
| Code gen | $0.565 | 8 | 14 |
| Agentic | $0.219 | 8 | 14 |

Workload mixes are defined on the [methodology page](/methodology/). 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 | 1340 |
| --- | --- |
| Context window | 262K |
| Max output | 80K |
| Input modes | text |
| Tool use | yes |
| Extended reasoning | yes |

Preserving recorded capabilities requires matching or beating these fields. [Full record for Trinity Large Thinking](/models/arcee-ai__trinity-large-thinking/), or [check Trinity Large Thinking against the whole catalogue](/check/arcee-ai__trinity-large-thinking/).

## Recorded capabilities preserved 11

Each option has a higher score or a lower price, with neither dimension worse under the listed workloads. It matches or beats Trinity Large Thinking on recorded context, maximum output, input modes, tool use and extended reasoning.

| # | Model | Intelligence | $/M | Holds under |
| --- | --- | --- | --- | --- |
| 1 | [GLM 5.3 Flash](/models/z-ai__glm-5.3-flash/) Z.ai | 1469.6 +129.6 | $0.238 | Balanced −39% Summarise −40% Chat −38% Code gen −38% Agentic −40% |
| 2 | [DeepSeek V4.1 Flash](/models/deepseek__deepseek-v4.1-flash/) DeepSeek | 1462.5 +122.5 | $0.182 | Balanced −53% Summarise −70% Chat −40% Code gen −36% Agentic −52% |
| 3 | [MiMo-V2.6-Flash](/models/xiaomi__mimo-v2.6-flash/) Xiaomi | 1456.4 +116.4 | $0.175 | Balanced −55% Summarise −52% Chat −63% Code gen −62% Agentic −64% |
| 4 | [Hy3](/models/tencent__hy3/) Tencent | 1440.7 +100.7 | $0.231 | Balanced −40% Summarise −45% Chat −37% Code gen −36% Agentic −40% |
| 5 | [Gemma 4 26B A4B](/models/google__gemma-4-26b-a4b-it/) Google | 1433.9 +93.9 | $0.127 | Balanced −67% Summarise −69% Chat −64% Code gen −64% Agentic −64% |
| 6 | [DeepSeek V4 Flash 0423](/models/deepseek__deepseek-v4-flash/) DeepSeek | 1432.1 +92.1 | $0.113 | Balanced −71% Summarise −67% Chat −75% Code gen −76% Agentic −72% |
| 7 | [MiMo-V2.5](/models/xiaomi__mimo-v2.5/) Xiaomi | 1427.5 +87.5 | $0.175 | Balanced −55% Summarise −52% Chat −63% Code gen −62% Agentic −64% |
| 8 | [GPT-6 Luna](/models/openai__gpt-6-luna/) OpenAI | 1391.5 +51.5 | $0.200 | Balanced −48% Summarise −58% Chat −44% Code gen −41% Agentic −51% |
| 9 | [Qwen3.8 27B](/models/qwen__qwen3.8-27b/) Qwen | 1440.7 +100.7 | $0.183 summarise | Summarise −18% |
| 10 | [GPT-5.6 Luna](/models/openai__gpt-5.6-luna/) OpenAI | 1431 +91 | $0.199 summarise | Summarise −11% |
| 11 | [GPT-5.4 Nano](/models/openai__gpt-5.4-nano/) OpenAI | 1372.1 +32.1 | $0.201 summarise | Summarise −10% |

## Alternatives with recorded capability losses 17

These improve score or price without worsening the other under the listed workloads, but reduce at least one recorded capability. Read the last column before switching.

| Model | Intelligence | $/M | Holds under | Recorded capability loss |
| --- | --- | --- | --- | --- |
| [Gemma 4 31B](/models/google__gemma-4-31b-it/) Google | 1443.4 +103.4 | $0.205 | Balanced −47% Summarise −31% Chat −41% Code gen −48% Agentic −18% | 80K → 16K max output |
| [DeepSeek V3.2](/models/deepseek__deepseek-v3.2/) DeepSeek | 1424.5 +84.5 | $0.290 | Balanced −25% Chat −35% Code gen −43% Agentic −9% | 262K → 164K context 80K → 66K max output |
| [DeepSeek V3.2 Exp](/models/deepseek__deepseek-v3.2-exp/) DeepSeek | 1422.4 +82.4 | $0.305 | Balanced −21% Chat −21% Code gen −37% | 262K → 164K context |
| [Qwen3 235B A22B Instruct 2507](/models/qwen__qwen3-235b-a22b-2507/) Qwen | 1419.3 +79.3 | $0.205 | Balanced −47% Summarise −49% Chat −34% Code gen −35% Agentic −28% | 80K → 16K max output no extended reasoning |
| [Qwen3 VL 235B A22B Instruct](/models/qwen__qwen3-vl-235b-a22b-instruct/) Qwen | 1420.1 +80.1 | $0.370 | Balanced −5% Summarise −7% | 80K → 33K max output no extended reasoning |
| [Qwen3 Next 80B A3B Instruct](/models/qwen__qwen3-next-80b-a3b-instruct/) Qwen | 1417.3 +77.3 | $0.268 | Balanced −31% Summarise −41% Chat −10% Code gen −10% Agentic −9% | no extended reasoning |
| [Step 3.5 Flash](/models/stepfun__step-3.5-flash/) StepFun | 1403 +63 | $0.150 | Balanced −61% Summarise −51% Chat −56% Code gen −61% Agentic −41% | 80K → 66K max output |
| [Qwen3.5-Flash](/models/qwen__qwen3.5-flash-02-23/) Qwen | 1397 +57 | $0.114 | Balanced −71% Summarise −67% Chat −65% Code gen −68% Agentic −57% | 80K → 66K max output |
| [Qwen3.5-35B-A3B](/models/qwen__qwen3.5-35b-a3b/) Qwen | 1394.4 +54.4 | $0.355 | Balanced −8% Summarise −30% Agentic −2% | 80K → 33K max output |
| [Qwen3 30B A3B Instruct 2507](/models/qwen__qwen3-30b-a3b-instruct-2507/) Qwen | 1384.1 +44.1 | $0.143 | Balanced −63% Summarise −55% Chat −58% Code gen −62% Agentic −45% | no extended reasoning |
| [GLM 4.5 Air](/models/z-ai__glm-4.5-air/) Z.ai | 1383.9 +43.9 | $0.310 | Balanced −20% Summarise −39% Chat −6% Code gen −2% Agentic −20% | 262K → 131K context |
| [gpt-oss-120b](/models/openai__gpt-oss-120b/) OpenAI | 1365.4 +25.4 | $0.065 | Balanced −83% Summarise −83% Chat −79% Code gen −80% Agentic −77% | 262K → 131K context |
| [Gemma 3 27B](/models/google__gemma-3-27b-it/) Google | 1357.8 +17.8 | $0.100 | Balanced −74% Summarise −62% Chat −73% Code gen −77% Agentic −58% | 262K → 131K context no extended reasoning |
| [GLM 4.7 Flash](/models/z-ai__glm-4.7-flash/) Z.ai | 1350.9 +10.9 | $0.145 | Balanced −63% Summarise −72% Chat −56% Code gen −54% Agentic −63% | 262K → 200K context |
| [Mercury 2](/models/inception__mercury-2/) Inception | 1355.2 +15.2 | $0.375 | Balanced −3% Summarise −6% Chat −7% Code gen −6% Agentic −13% | 262K → 128K context 80K → 50K max output |
| [Qwen3 32B](/models/qwen__qwen3-32b/) Qwen | 1340.1 tie | $0.130 | Balanced −66% Summarise −60% Chat −61% Code gen −65% Agentic −50% | 262K → 131K context 80K → 16K max output |
| [Qwen3 Next 80B A3B Thinking](/models/qwen__qwen3-next-80b-a3b-thinking/) Qwen | 1368.3 +28.3 | $0.203 summarise | Summarise −9% | 80K → 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 ±10.47 points, so a gap smaller than that is marked *tie* rather than an improvement — see [significance bands](/significance/).
 - 204 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.
 - Models with no higher-scoring or cheaper alternative that is no worse on the other axis are on the [value frontier](/frontier/). Models with such an alternative are [listed here](/alternatives/).

## Continue your investigation

 - [Check requirements](/check/)
- [Compare exact differences](/compare/)
- [Set a quality floor](/cheapest-at/)
- [Inspect tier boundaries](/cliffs/)