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Comparison · 3 models · Updated Nov 2, 2026

Gemini 2.0 Flash-Lite vs Command R7B Arabic vs Nova Lite

Gemini 2.0 Flash-Lite comes out ahead, 82 to 75 and 65 on our weighted score, though Command R7B Arabic is 41% cheaper per token.

  1. Our pick

    Google

    Gemini 2.0 Flash-Lite

    Released Dec 11, 2024

    82/100
    • ECI—
    • Price$0.064 / $0.255
    • Context1.05M
  2. Cohere

    Command R7B Arabic

    Released Feb 27, 2025

    65/100
    • ECI—
    • Price$0.037 / $0.15
    • Context128K
  3. Amazon

    Nova Lite

    Released Dec 3, 2024

    75/100
    • ECI—
    • Price$0.06 / $0.24
    • Context300K
01 — Verdict

Gemini 2.0 Flash-Lite is our pick

Gemini 2.0 Flash-Lite is the better all-round choice, scoring 82/100 against Nova Lite (75) and Command R7B Arabic (65). It leads on inputs & features and context window. Command R7B Arabic wins on price. The score weighs price 50%, inputs & features 30%, context window 20%. None of the shared benchmarks cover every model here yet, so capability is left out of this verdict.

  • CapabilityNot enough dataNo independent benchmark covers every model here yet
  • Lowest priceCommand R7B ArabicCommand R7B Arabic $0.066 · Nova Lite $0.105 · Gemini 2.0 Flash-Lite $0.111 per 1M tokens (3:1 blend)
  • Longest contextGemini 2.0 Flash-LiteGemini 2.0 Flash-Lite 1,048,576 · Nova Lite 300,000 · Command R7B Arabic 128,000 tokens
  • Widest inputsGemini 2.0 Flash-LiteGemini 2.0 Flash-Lite: Text, Images, PDFs, Audio, Video · Command R7B Arabic: Text · Nova Lite: Text, Images, PDFs, Video
  • Self-hostingCommand R7B ArabicPublishes downloadable weights
How the score is built
MeasureWeightGemini 2.0 Flash-LiteCommand R7B ArabicNova Lite
Price50%9110092
Inputs & features30%803570
Context window20%612439
Overall100%82/10065/10075/100

Left out because at least one model lacks the data: capability. The remaining weights were rescaled.

02 — Side by side

Every spec in one table

Highlighted cells lead their row. Dashes mean the data is not published.

Gemini 2.0 Flash-Lite vs Command R7B Arabic vs Nova Lite specifications side by side
SpecificationGemini 2.0 Flash-LiteGoogleCommand R7B ArabicCohereNova LiteAmazon
Capability
Capabilities Index (ECI)———
ECI rank———
Price per million tokens
Input$0.064$0.037 (best)$0.06
Output$0.255$0.15 (best)$0.24
Cached input——$0.015
Blended (3:1)$0.111$0.066 (best)$0.105
Long-context rateSame rateSame rateSame rate
Price sourceMedian of 2 providersOfficial Cohere APIOfficial Amazon Bedrock API
Limits
Context window1,048,576 tokens (best)128,000 tokens300,000 tokens
Max output8,192 tokens4,000 tokens10,000 tokens (best)
Inputs and features
TextYesYesYes
ImagesYesNoYes
PDFsYesNoYes
AudioYesNoNo
VideoYesNoYes
ReasoningNoNoNo
Tool callingYesYesYes
Structured outputNoYesNo
Availability
WeightsProprietaryOpenProprietary
API model ID—command-r7b-arabic-02-2025amazon.nova-lite-v1:0
API providers318 (best)
ReleasedDec 11, 2024Feb 27, 2025Dec 3, 2024
Knowledge cutoffJun 2024Jun 1, 2024Oct 2024
03 — Cost

What would a month cost?

Enter your expected volume in millions of tokens. List prices only; caching and batch discounts would lower these.

  • Gemini 2.0 Flash-Lite$1.15
  • Command R7B Arabic$0.675
  • Nova Lite$1.08
04 — Questions

Which should you choose?

Which is better: Gemini 2.0 Flash-Lite, Command R7B Arabic or Nova Lite?

Gemini 2.0 Flash-Lite is the better all-round choice, scoring 82/100 against Nova Lite (75) and Command R7B Arabic (65). It leads on inputs & features and context window. Command R7B Arabic wins on price. The score weighs price 50%, inputs & features 30%, context window 20%. None of the shared benchmarks cover every model here yet, so capability is left out of this verdict.

Which is cheaper, Gemini 2.0 Flash-Lite, Command R7B Arabic or Nova Lite?

Command R7B Arabic is cheaper at $0.037 input / $0.15 output per million tokens (official Cohere API price). Nova Lite costs $0.06 input / $0.24 output per million tokens (official Amazon Bedrock API price); Gemini 2.0 Flash-Lite costs $0.064 input / $0.255 output per million tokens (median across 2 API providers). At a typical mix of three input tokens to one output token, that is $0.066 per million tokens for Command R7B Arabic versus $0.105 for Nova Lite (1.6× as much) and $0.111 for Gemini 2.0 Flash-Lite (1.7× as much).

Which scores higher on benchmarks?

There is no independent benchmark that covers all three models yet. Gemini 2.0 Flash-Lite has not been scored yet, Command R7B Arabic has not been scored yet and Nova Lite has not been scored yet.

Which is better for coding?

There are no published SWE-bench Verified results for Gemini 2.0 Flash-Lite, Command R7B Arabic and Nova Lite yet, so there is no like-for-like coding score. Test both on a sample of your own tasks. All three support tool calling for agent workflows.

Which has the bigger context window?

Gemini 2.0 Flash-Lite has the largest context window at 1,048,576 tokens, against 300,000 for Nova Lite and 128,000 for Command R7B Arabic. Maximum output per response: Gemini 2.0 Flash-Lite up to 8,192, Command R7B Arabic up to 4,000, Nova Lite up to 10,000 tokens.

Which can read images, PDFs, audio or video?

Gemini 2.0 Flash-Lite accepts text, images, PDFs, audio and video; Command R7B Arabic accepts text; Nova Lite accepts text, images, PDFs and video. Gemini 2.0 Flash-Lite handles the widest range of inputs.

Are any of these open source?

Command R7B Arabic publishes its weights and can be self-hosted; Gemini 2.0 Flash-Lite and Nova Lite is proprietary.

Which is newer?

Command R7B Arabic is the newest, released Feb 27, 2025. Gemini 2.0 Flash-Lite came out Dec 11, 2024; Nova Lite came out Dec 3, 2024. Knowledge cutoff: Gemini 2.0 Flash-Lite Jun 2024, Command R7B Arabic Jun 1, 2024, Nova Lite Oct 2024.

How do you decide the winner?

Each model gets a 0–100 score on capability (50%, independent benchmark results); price (25%, blended price per million tokens (3 input : 1 output), log scale); inputs & features (15%, image, PDF, audio and video input, tool calling, structured output and reasoning); context window (10%, maximum tokens per request, log scale). Dimensions missing for any model are dropped and the remaining weights rescaled, so every model is judged on the same evidence. Specs and prices come from public model listings and the labs’ own API pages; capability scores come from independent benchmark runs. Data updated Nov 2, 2026.