Amazon Nova Pro vs Amazon Nova Lite

So, I was testing DeepSeek-R1 with a math problem I found in a textbook for 9-year-olds **(yes, really)**, and the model managed to crack it.

The problem was:

`"Find two 3-digit palindromic numbers that add up to a 4-digit palindromic number. Note: the first digit of any of these numbers can't be 0."`

[R1 starts thinking...](https://preview.redd.it/ml5hnng3rwge1.jpg?width=1800&format=pjpg&auto=webp&s=1456610eeff8d8b9a122d86fbb44967f84f682d9)

Now, here’s where it gets interesting. R1 thought for a bit, found the correct answer in its `<think></think>` block, then went ahead to output it—but made a mistake.

[R1 makes a mistake...](https://preview.redd.it/77bke6q1swge1.jpg?width=1800&format=pjpg&auto=webp&s=d6eac07677fe576be9e699776a2134cba1d15c62)

Before even finishing its response, it caught its own error, backtracked, and corrected itself on the fly outside of the`<think></think>` block.

[R1 corrects itself...](https://preview.redd.it/yc3zjamsswge1.jpg?width=1800&format=pjpg&auto=webp&s=903d42998593e95a68ff32006b7bac6335df9f1e)

[R1's final answer.](https://preview.redd.it/j8vgvxn3twge1.jpg?width=1800&format=pjpg&auto=webp&s=b189fce4a099ed9182b315c2164a1071a4a32104)

[DeepSeek-R1 complete answer.](https://pastebin.com/0Ayv77LN)

Regarding the problem, **no other LLM solved it, except for** [**OpenAI o1**](https://pastebin.com/YCRR521W).

So now I’m wondering—**what's holding them back?** Is it the tokenizer's weaknesses? The sampling parameters (even when all where at the recommended settings they failed)? Or maybe, just maybe, non-thinking LLMs are really that bad at math?

Would love to hear thoughts on this.

Unsuccessful attemps by other models:

* [chatgpt-4o-latest-20241120](https://pastebin.com/r8VKHrcA)
* [claude-3-5-sonnet-20241022](https://pastebin.com/tXc7wGVz)
* [phi-4](https://pastebin.com/zGzQJ8B5)
* [amazon-nova-pro-v1.0](https://pastebin.com/vt54UFBe)
* [gemini-exp-1206](https://pastebin.com/eSN4y6E0)
* [llama-3.1-405b-instruct-bf16](https://pastebin.com/jVj1KcMF)
* [qwen-max-2025-01-25](https://pastebin.com/ZRLfhEfU)

That recent post about Carnegie Mellon's "AI disaster" https://www.reddit.com/r/singularity/comments/1k5s2iv/carnegie_mellon_staffed_a_fake_company_with_ai/

demonstrates perfectly how r/singularity rushes to embrace doomer narratives without actually reading the articles they're celebrating. If anyone bothered to look beyond the clickbait headline, they'd see that this study actually showcases how fucking close we are to fully automated employees and the recursive self improvement loop of automated machine learning research!!!!!

The important context being overlooked by everyone in the comments is that this study tested outdated models due to research and publishing delays.
Here were the models being tested:

- Claude-3.5-Sonnet(3.6)
- Gemini-2.0-Flash
- GPT-4o
- Gemini-1.5-Pro
- Amazon-Nova-Pro-v1
- Llama-3.1-405b
- Llama-3.3-70b
- Qwen-2.5-72b
- Llama-3.1-70b
- Qwen-2-72b

Of all models tested, Claude-3.5-Sonnet was the only one even approaching reasoning or agentic capabilities, and that was an early experimental version.

Despite these limitations, Claude still successfully completed 25% of its assigned tasks.

Think about the implications of a first-generation non-agentic, non-reasoning AI is already capable of handling a quarter of workplace responsibilities all within the context of what Anthropic announced yesterday that **fully AI employees are only a year away** (!!!):

https://www.axios.com/2025/04/22/ai-anthropic-virtual-employees-security

If anything this Carnegie Mellon study only further validates that what Anthropic is claiming is true and that we should utterly heed their company when their company announces that it expects "AI-powered virtual employees to begin roaming corporate networks in the next year" and take it fucking seriously when they say that these won't be simple task-focused agents but virtual employees with "their own 'memories,' their own roles in the company and even their own corporate accounts and passwords".

The r/singularity community seems more interested in celebrating perceived AI failures than understanding the actual trajectory of progress. What this study really shows is that even early non-reasoning, non-agentic models demonstrate significant capability, and, contrary to what the rabbid luddites in r/singularity would have you believe, only further substantiates rumours that soon these AI employees will have "a level of autonomy that far exceeds what agents have today" and will operate independently across company systems, making complex decisions without human oversight and completely revolutionize the world as we know it more or less overnight.

There are currently 481 models listed on the [arena.ai](http://arena.ai) website.

Here's the full list:

amazon.nova-pro-v1:0

anonymous-0410

anonymous-1111

anonymous-1218

anonymous-1221

anonymous-1800

anonymous-1815

anonymous-1825

anonymous-1835

apex-atlas

april26-chatbot1

april26-chatbot2

arastradero

atlas

autobear

badger

basalt-0303-1

basalt-0422-1

baseliner

beluga-0311-1

beluga-0413-1

blackhawk

blue-forge

botbot2

chatgpt-image-latest-high-fidelity (20251216)

chipmunk

chives

citrus

claude-3-5-sonnet-20241022

claude-3-7-sonnet-20250219

claude-3-7-sonnet-20250219-thinking-32k

claude-haiku-4-5-20251001

claude-opus-4-1-20250805

claude-opus-4-1-20250805-thinking-16k

claude-opus-4-1-search

claude-opus-4-20250514

claude-opus-4-20250514-thinking-16k

claude-opus-4-5-20251101

claude-opus-4-5-20251101-thinking-32k

claude-opus-4-5-search

claude-opus-4-6

claude-opus-4-6-search

claude-opus-4-6-thinking

claude-opus-4-7

claude-opus-4-7-search

claude-opus-4-7-thinking

claude-opus-4-search

claude-sonnet-4-20250514

claude-sonnet-4-20250514-thinking-32k

claude-sonnet-4-5-20250929

claude-sonnet-4-5-20250929-thinking-32k

claude-sonnet-4-5-search

claude-sonnet-4-6

claude-sonnet-4-6-search

clawl

clinkz

cloud-buddy

dall-e-3

dart-frog-0206

deep-octo

deepseek-v4-flash

deepseek-v4-flash-thinking

deepseek-v4-pro

deepseek-v4-pro-thinking

devstral-2

devstral-medium-2507

dialogue

dola-seed-2.0-preview-text

dola-seed-2.0-preview-vision

dola-seed-2.0-pro-text

dola-seed-2.0-pro-vision

dove

duomo-1-hero

EB45-turbo

EB45-vision

ember

emu

epilogue

ernie-5.0-0110

ernie-5.0-preview-1220

ernie-exp-251023

ernie-exp-251024

ernie-exp-251025

ernie-exp-251026

ernie-exp-251027

ernie-exp-vl-251016

ernie-image

eureka

february26-chatbot2

february26-chatbot3

february26-chatbot4

flashbrown-a

flashbrown-b

flow-state

flow-state-2

flow-state-3

flux-1-kontext-dev

flux-1-kontext-max

flux-1-kontext-pro

flux-2-dev

flux-2-flex

flux-2-klein-4b

flux-2-klein-9b

flux-2-max

flux-2-pro

flying-octopus

frenchfry

frieza

gallant

gallery

gcps-fast

gemini-2.0-flash-001

gemini-2.5-flash

gemini-2.5-flash-image-preview (nano-banana)

gemini-2.5-pro

gemini-2.5-pro-grounding

gemini-2.5-pro-grounding-exp

gemini-3-flash

gemini-3-flash (thinking-minimal)

gemini-3-flash-grounding

gemini-3-pro

gemini-3-pro-image-preview-2k (nano-banana-pro)

gemini-3.1-flash-image-preview (nano-banana-2) \[web-search\]

gemini-3.1-flash-lite-preview

gemini-3.1-pro

gemini-3.1-pro-grounding

gemini-3.1-pro-preview

gemma-3-27b-it

gemma-3n-e4b-it

glm-4.7

glm-4.7-flash

glm-5

glm-5.1

glm-5v-turbo

globe\_2

gpt-4.1-2025-04-14

gpt-4.1-mini-2025-04-14

gpt-5-chat

gpt-5-high

gpt-5-high-new-system-prompt

gpt-5-high-no-system-prompt

gpt-5-medium

gpt-5-mini-high

gpt-5-nano-high

gpt-5-search

gpt-5.1

gpt-5.1-codex

gpt-5.1-codex-max

gpt-5.1-codex-mini

gpt-5.1-high

gpt-5.1-medium

gpt-5.1-search

gpt-5.1-search-sp

gpt-5.2

gpt-5.2-chat-latest

gpt-5.2-codex

gpt-5.2-high

gpt-5.2-search

gpt-5.2-search-non-reasoning

gpt-5.3-chat-latest

gpt-5.3-codex

gpt-5.4

gpt-5.4-high

gpt-5.4-high-no-system-prompt

gpt-5.4-medium

gpt-5.4-mini-high

gpt-5.4-nano-high

gpt-5.4-no-system-prompt

gpt-5.4-search

gpt-5.5

gpt-5.5-high

gpt-5.5-search

gpt-image-1

gpt-image-1-high-fidelity

gpt-image-1-mini

gpt-image-1.5-high-fidelity

gpt-image-2 (medium)

gpt-oss-120b

gpt-oss-20b

grok-3-mini-beta

grok-3-mini-high

grok-4-0709

grok-4-1-fast-non-reasoning

grok-4-1-fast-reasoning

grok-4-1-fast-search

grok-4-fast-chat

grok-4-fast-reasoning

grok-4-fast-search

grok-4-search

grok-4.1

grok-4.1-thinking

grok-4.20-beta-0309-reasoning

grok-4.20-beta1

grok-4.20-multi-agent-beta-0309

grok-code-fast-1

grok-imagine-image

grok-imagine-image-pro

grok-imagine-video

hailuo-02-fast

hailuo-02-pro

hailuo-02-standard

hailuo-2.3

hailuo-2.3-fast

happy-friday-testing-1

happy-friday-testing-2

hearth

hidream-e1.1

hofburg\_2

hofburg\_2\_alt

hofburg\_3

hofburg\_4

hofburg\_5

hofburg\_5\_alt

hofburg-1

hunyuan-hy3-preview

hunyuan-image-2.1

hunyuan-image-3.0

hunyuan-image-3.0-fal

hunyuan-t1-20250711

hunyuan-video-1.5

hunyuan-vision-1.5-thinking

ibm-granite-h-small

ideogram-v3-quality

imagen-3.0-generate-002

imagen-4.0-fast-generate-001

imagen-4.0-generate-001

imagen-4.0-ultra-generate-001

intellect-3

jester

jumbo-dungeness

juniper

k2

kandinsky-5.0-i2v-pro

kandinsky-5.0-t2v-lite

kandinsky-5.0-t2v-pro

karyu

KAT-Coder-Pro-V1

ketchup-v2

kimi-k2-0711-preview

kimi-k2-0905-preview

kimi-k2-thinking-turbo

kimi-k2.5

kimi-k2.5-instant

kimi-k2.6

kiteki

kiwi-do

kiwire

kizen-alpha

kizen-beta

kling-2.5-turbo-1080p

kling-2.6-pro

kling-2.6-standard

kling-image-o1

kling-o1-pro

kling-o3-pro

kling-v2.1-master

kling-v2.1-standard

kling-v3

leepwal

left-bank

ling-1t

ling-1t-1031

ling-2.5-1t

ling-flash-2.0

llama-3.3-70b-instruct

longcat-flash-chat

ltx-2-19b

lucid-origin

mammoth-newt-0206

mammoth-newt-0226

march26-chatbot1

march26-chatbot1-public

march26-chatbot2

march26-chatbot3

markhor

Max

mercury

mercury-2

micro-mango

mimo-v2-flash

mimo-v2-flash (thinking)

mimo-v2-omni

mimo-v2-pro

mimo-v2.5

mimo-v2.5-pro

minicpm-sala

minimax-m1

minimax-m2

minimax-m2-preview

minimax-m2.1-preview

minimax-m2.5

mistral-large-3

mistral-medium-2505

mistral-medium-2508

mistral-small-2506

mistral-small-2603

mistral-small-3.1-24b-instruct-2503

mochi-v1

model-x

model-x-2

molmo-2-8b

monologue

monster

monterey

neon

nightride-on

nightride-on-v2

nova-2-lite

nvidia-nemotron-3-nano-30b-a3b-bf16

o3-2025-04-16

o3-mini

o3-search

o4-mini-2025-04-16

olmo-3-32b-think

olmo-3.1-32b-instruct

olmo-3.1-32b-think

orion

p-image

p-image-edit

paper-lantern

pebble-1

pebble-2

pepper

photon

pika-v2.2

pine

pisces-0226d

pisces-0309

pisces-0309-vision

pisces-0309b

pisces-0309c

pisces-0309d

pisces-0318-text

pisces-0318-vision

pisces-0320

pisces-llm-0130

pixel-parrot

pixverse-v5.6

ppl-sonar-reasoning-pro-high

prologue

pteronura

pulse

queen-bee

quiet\_sand

qwen-image-2.0

qwen-image-2.0-pro

qwen-image-2512

qwen-image-edit

qwen-image-edit-2511

qwen-image-prompt-extend

qwen-vl-max-2025-08-13

qwen3-235b-a22b

qwen3-235b-a22b-instruct-2507

qwen3-235b-a22b-no-thinking

qwen3-235b-a22b-thinking-2507

qwen3-30b-a3b

qwen3-30b-a3b-instruct-2507

qwen3-coder-480b-a35b-instruct

qwen3-max-2025-09-23

qwen3-max-2025-09-26

qwen3-max-2025-10-30

qwen3-max-preview

qwen3-max-thinking

qwen3-next-80b-a3b-instruct

qwen3-next-80b-a3b-thinking

qwen3-omni-flash

qwen3-vl-235b-a22b-instruct

qwen3-vl-235b-a22b-thinking

qwen3-vl-8b-instruct

qwen3-vl-8b-thinking

qwen3.5-122b-a10b

qwen3.5-122b-a10b-code

qwen3.5-27b

qwen3.5-27b-code

qwen3.5-35b-a3b

qwen3.5-35b-a3b-code

qwen3.5-397b-a17b

qwen3.5-flash

qwen3.6-plus

qwen3.6-plus-preview

qwq-32b

raptor-1.8-0120

raptor-1123

raptor-1124

ray-3

ray2

recraft-v3

recraft-v4

redwood

reve-v1.1

reve-v1.1-fast

ring-1t

ring-2.5-1t

ring-flash-2.0

rising-sun

robin

robin-high

rotten-apple

runway-gen-4.5

runway-gen4

runway-gen4-aleph

runway-gen4-turbo

scorch

seed-1.8

seedance-v1-lite

seedance-v1-pro

seedance-v1.5-pro

seededit-3.0

seedream-3

seedream-4-high-res-fal

seedream-4.5

seedream-5.0-lite

shakshouka

significant-otter

snowflake

soft-shell

solar-eclipse

sora

sora-2

sora-2-pro

spark

sphinx

spire

star-drift

steed-0217

step-3

step-3-mini-2511

step-3.5-flash

stephen-v2

stephen-vision-csfix

sungod

sunshine-ai

super-cara

super-gcp

tatertot

trinity-large

trinity-large-thinking

velo

veo-2

veo-3

veo-3-audio

veo-3-fast

veo-3-fast-audio

veo-3.1-audio

veo-3.1-audio-1080p

veo-3.1-audio-4k

veo-3.1-fast-audio

veo-3.1-fast-audio-1080p

veo-3.1-fast-audio-4k

vidu-q2-image

vierra

viper

vortex

vulcan

waffle

wan-v2.2-a14b

wan-vace

wan2.5-i2i-preview

wan2.5-i2v-preview

wan2.5-preview

wan2.5-t2i-preview

wan2.5-t2v-preview

wan2.6-i2v

wan2.6-image

wan2.6-t2i

wan2.6-t2v

wan2.7-i2v

wan2.7-image

wan2.7-image-pro

wan2.7-t2v

whisperfall

wild-bits

yivon-beta

yotta-nexus

z-image

zephyr

zero-prism

zeylu-alpha

zeylu-beta

zorik

Unfortunately, the list of models available for selection in direct and side-by-side mode is much smaller :(

Amazon just launched Nova 2 Lite models on Bedrock.

Now, you can use those models directly with Claude Code, and set automatic preferences on when to invoke the model for specific coding scenarios. Sample config below. This way you can mix/match different models based on coding use cases. Details in the demo folder here: [https://github.com/katanemo/archgw/tree/main/demos/use\_cases/claude\_code\_router](https://github.com/katanemo/archgw/tree/main/demos/use_cases/claude_code_router)

if you think this is useful, then don't forget to the star the project 🙏

# Anthropic Models
- model: anthropic/claude-sonnet-4-5
access_key: $ANTHROPIC_API_KEY
routing_preferences:
- name: code understanding
description: understand and explain existing code snippets, functions, or libraries

- model: amazon_bedrock/us.amazon.nova-2-lite-v1:0
default: true
access_key: $AWS_BEARER_TOKEN_BEDROCK
base_url: https://bedrock-runtime.us-west-2.amazonaws.com
routing_preferences:
- name: code generation
description: generating new code snippets, functions, or boilerplate based on user prompts or requirements

- model: anthropic/claude-haiku-4-5
access_key: $ANTHROPIC_API_KEY

# Text & Chat Models (LLMs)

# Google (Gemini & Gemma)

* **gemini-2.5-pro**
* gemini-2.5-pro-grounding-exp
* gemini-2.5-flash
* gemini-2.5-flash-preview-09-2025
* gemini-2.5-flash-lite-preview-09-2025-no-thinking
* gemini-2.5-flash-lite-preview-06-17-thinking
* gemini-3-pro
* gemini-2.0-flash-001
* gemma-3-27b-it
* gemma-3n-e4b-it

# OpenAI (GPT & O-Series)

* **gpt-5.1** / gpt-5.1-high
* **gpt-5-chat**
* gpt-5-high / gpt-5-high-new-system-prompt / gpt-5-high-no-system-prompt
* gpt-5-mini-high / gpt-5-nano-high
* **chatgpt-4o-latest-20250326**
* gpt-4.1-2025-04-14 / gpt-4.1-mini-2025-04-14
* gpt-oss-120b / gpt-oss-20b
* **o3-2025-04-16** / o3-mini
* **o4-mini-2025-04-16**

# Anthropic (Claude)

* **claude-3-7-sonnet-20250219** (+ thinking/thinking-32k)
* **claude-3-5-sonnet-20241022**
* claude-3-5-haiku-20241022
* **claude-opus-4-5-20251101** (+ thinking-32k)
* claude-sonnet-4-5-20250929 (+ thinking-32k)
* claude-haiku-4-5-20251001
* claude-opus-4-1-20250805 (+ thinking-16k)
* claude-opus-4-20250514 (+ thinking-16k)
* claude-sonnet-4-20250514 (+ thinking-32k)

# xAI (Grok)

* grok-3-mini-beta / grok-3-mini-high
* **grok-4.1** / grok-4.1-thinking
* grok-4-1-fast-reasoning / grok-4-1-fast-non-reasoning
* grok-4-0709
* grok-4-fast-chat / grok-4-fast-reasoning

# Alibaba (Qwen)

* qwen3-max-2025-09-23 / 09-26 / 10-20
* qwen3-max-preview / qwen3-max-thinking
* qwen3-next-80b-a3b-instruct / thinking
* qwen3-235b-a22b (+ instruct/thinking/no-thinking)
* qwen3-30b-a3b (+ instruct)
* qwen3-coder-480b-a35b-instruct
* qwen3-omni-flash
* qwq-32b
* Vision Understanding: qwen3-vl-235b-a22b (+instruct/thinking), qwen3-vl-8b (+instruct/thinking), qwen-vl-max-2025-08-13

# DeepSeek

* deepseek-v3.2
* deepseek-v3.2-thinking
* deepseek-v3-0324

# Meta (Llama)

* llama-3.3-70b-instruct
* llama-4-maverick-17b-128e-instruct

# Mistral

* mistral-large-3
* mistral-medium-2505 / 2508
* mistral-small-2506 / 3.1-24b-instruct-2503
* magistral-medium-2506

# Other Text Models

* **Baidu:** ernie-5.0-preview (1103/1120), ernie-exp (various dates)
* **Zhipu:** glm-4.5, glm-4.5-air, glm-4.5v, glm-4.6
* **MiniMax:** minimax-m1, minimax-m2, minimax-m2-preview
* **Tencent:** hunyuan-t1-20250711, hunyuan-vision-1.5-thinking
* **Amazon:** nova-2-lite, amazon-nova-experimental-chat, amazon.nova-pro-v1:0
* **Misc:** command-a-03-2025, ling-1t, ling-flash-2.0, step-3, ring-flash-2.0, intellect-3

# Image Generation Models

# Google (Imagen/Gemini)

* **gemini-3-pro-image-preview** (Standard, 2k, and 4k versions)
* gemini-2.5-flash-image-preview
* gemini-2.0-flash-preview-image-generation
* imagen-4.0-generate-001
* imagen-4.0-fast-generate-001
* imagen-4.0-ultra-generate-001
* imagen-3.0-generate-002

# Black Forest Labs (Flux)

* flux-2-pro
* flux-2-dev
* flux-2-flex
* flux-1-kontext-pro
* flux-1-kontext-dev
* flux-1-kontext-max

# OpenAI

* dall-e-3
* gpt-image-1
* gpt-image-1-mini
* gpt-image-1-high-fidelity

# Alibaba (Qwen Image)

* qwen-image-edit
* qwen-image-prompt-extend

# Tencent (Hunyuan)

* hunyuan-image-3.0
* hunyuan-image-3.0-fal
* hunyuan-image-2.1

# Wan / Video Models

* **wan2.5-preview**
* wan2.5-t2i-preview (Text to Image)
* wan2.5-i2i-preview (Image to Image)
* vidu-q2-image
* reve-v1 / reve-fast-edit

# Other Visual Models

* recraft-v3
* ideogram-v3-quality
* seedream-3 / seedream-4.5 / seedream-4-high-res-fal
* seededit-3.0
* mai-image-1
* photon
* lucid-origin
* hazel-gen-2 / 4
* hazel-edit-2 / 6
* hidream-e1.1
* tangerine
* ghost-pepper

# Hidden / Anonymous / Battle Models

These are internal codenames, blind test models, or obfuscated names specific to the Arena.

**The "Beluga/Phantom" Series:**

* beluga-1128-1
* phantom-1203-1
* phantom-mm-1125-1

**The "Raptor" Series:**

* raptor (base, 1110, 1119, 1123, 1124, 1202)
* raptor-llm (1017, 1024, 1125, 1205)
* raptor-vision (1015, 1107)

**The "EB / X1" Series:**

* EB45-turbo
* EB45-turbo-vl-0906
* EB45-vision
* x1-1-preview-0915
* x1-turbo-0906

**Anonymous IDs:**

* anonymous-1111, 1010, 915, 922, 925
* lmarena-internal-test-only
* not-a-new-model
* stephen-v2 / stephen-vision-csfix

**Abstract Codenames:**

* aegis-core, blackhawk, blitzphase, bridge-mind, dark-dragon, dashspark, evo-logic
* flashstride, flying-octopus, frame-flow, gauss, holo-scope, integrated-info
* leepwal, micro-mango, monster, monterey, neon, newton
* nightride-on / v2, rain-drop, redwood, route66, rushstream
* seahawk, silentnova, silvandra, skyhawk, sunshine-ai
* swiftflare, voltwhirl, viper, whisperfall, winter-wind

None of the MS models seem to be working for me. I get an error like:

`[API Error: 404 litellm.NotFoundError: NotFoundError: OpenrouterException - {"error":{"message":"No endpoints found that support tool use. To learn more about provider routing, visit:`
`https://openrouter.ai/docs/guides/routing/provider-selection","code":404}}. Received Model Group=blackboxai/microsoft/phi-4Available Model Group Fallbacks=None]`

Separately, the amazon/nova-lite-v1 model is s\*\*t... Offers vague recommendations and no specific fix for any code.