ZMIME
Comparison · 3 models · Updated Nov 2, 2026

Qwen2.5-Coder-32B-Instruct vs Gemma 2 27B vs Aya Expanse 32B

Qwen2.5-Coder-32B-Instruct comes out ahead, 39 to 32 and 28 on our weighted score, though Gemma 2 27B is 13% cheaper per token.

  1. Our pick

    Alibaba (Qwen)

    Qwen2.5-Coder-32B-Instruct

    Released Nov 12, 2024

    39/100
    • ECI—
    • Price$0.66 / $1.00
    • Context131K
    Full specs Remove Qwen2.5-Coder-32B-Instruct

  2. Google

    Gemma 2 27B

    Released Jul 13, 2024

    28/100
    • ECI122.1
    • Price$0.65 / $0.65
    • Context8K
    Full specs Remove Gemma 2 27B

  3. Cohere

    Aya Expanse 32B

    Released Oct 24, 2024

    32/100
    • ECI—
    • Price$0.50 / $1.50
    • Context128K
    Full specs Remove Aya Expanse 32B
01 — Verdict

Qwen2.5-Coder-32B-Instruct is our pick

Qwen2.5-Coder-32B-Instruct is the better all-round choice, scoring 39/100 against Aya Expanse 32B (32) and Gemma 2 27B (28). It leads on inputs & features. Gemma 2 27B 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 priceGemma 2 27BGemma 2 27B $0.65 · Qwen2.5-Coder-32B-Instruct $0.745 · Aya Expanse 32B $0.75 per 1M tokens (3:1 blend)
  • Longest contextQwen2.5-Coder-32B-InstructQwen2.5-Coder-32B-Instruct 131,072 · Aya Expanse 32B 128,000 · Gemma 2 27B 8,192 tokens
  • Widest inputsSame inputsQwen2.5-Coder-32B-Instruct: Text · Gemma 2 27B: Text · Aya Expanse 32B: Text
  • Self-hostingAll open weightsEvery model here can be downloaded and run on your own hardware
How the score is built
MeasureWeightQwen2.5-Coder-32B-InstructGemma 2 27BAya Expanse 32B
Price50%545653
Inputs & features30%2500
Context window20%25024
Overall100%39/10028/10032/100

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.

Qwen2.5-Coder-32B-Instruct vs Gemma 2 27B vs Aya Expanse 32B specifications side by side
SpecificationQwen2.5-Coder-32B-InstructAlibaba (Qwen)Gemma 2 27BGoogleAya Expanse 32BCohere
Capability
Capabilities Index (ECI)—122.1—
ECI rank—#152 of 165—
GPQA DiamondGraduate-level science questions—36.5%—
OTIS Mock AIME 2024–2025Competition mathematics—1.4%—
Price per million tokens
Input$0.66$0.65$0.50 (best)
Output$1.00$0.65 (best)$1.50
Cached input———
Blended (3:1)$0.745$0.65 (best)$0.75
Long-context rateSame rateSame rateSame rate
Price sourceMedian of 7 providersMedian of 3 providersOfficial Cohere API
Limits
Context window131,072 tokens (best)8,192 tokens128,000 tokens
Max output8,192 tokens (best)2,048 tokens4,000 tokens
Inputs and features
TextYesYesYes
ImagesNoNoNo
PDFsNoNoNo
AudioNoNoNo
VideoNoNoNo
ReasoningNoNoNo
Tool callingYesNoNo
Structured outputNoNoNo
Availability
WeightsOpenOpenOpenCC-BY-NC-4.0
API model ID——c4ai-aya-expanse-32b
API providers7 (best)32
ReleasedNov 12, 2024Jul 13, 2024Oct 24, 2024
Knowledge cutoff—Jun 30, 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.

  • Qwen2.5-Coder-32B-Instruct$8.60
  • Gemma 2 27B$7.80
  • Aya Expanse 32B$8.00
04 — Questions

Which should you choose?

Which is better: Qwen2.5-Coder-32B-Instruct, Gemma 2 27B or Aya Expanse 32B?

Qwen2.5-Coder-32B-Instruct is the better all-round choice, scoring 39/100 against Aya Expanse 32B (32) and Gemma 2 27B (28). It leads on inputs & features. Gemma 2 27B 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, Qwen2.5-Coder-32B-Instruct, Gemma 2 27B or Aya Expanse 32B?

Gemma 2 27B is cheaper at $0.65 input / $0.65 output per million tokens (median across 3 API providers). Qwen2.5-Coder-32B-Instruct costs $0.66 input / $1.00 output per million tokens (median across 7 API providers); Aya Expanse 32B costs $0.50 input / $1.50 output per million tokens (official Cohere API price). At a typical mix of three input tokens to one output token, that is $0.65 per million tokens for Gemma 2 27B versus $0.745 for Qwen2.5-Coder-32B-Instruct (1.1× as much) and $0.75 for Aya Expanse 32B (1.2× as much).

Which scores higher on benchmarks?

There is no independent benchmark that covers all three models yet. Qwen2.5-Coder-32B-Instruct has not been scored yet, Gemma 2 27B has an ECI of 122.1 and Aya Expanse 32B has not been scored yet.

Which is better for coding?

There are no published SWE-bench Verified results for Qwen2.5-Coder-32B-Instruct, Gemma 2 27B and Aya Expanse 32B yet, so there is no like-for-like coding score. Test both on a sample of your own tasks. Note that Gemma 2 27B and Aya Expanse 32B does not support tool calling, which most coding agents need.

Which has the bigger context window?

Qwen2.5-Coder-32B-Instruct has the largest context window at 131,072 tokens, against 128,000 for Aya Expanse 32B and 8,192 for Gemma 2 27B. Maximum output per response: Qwen2.5-Coder-32B-Instruct up to 8,192, Gemma 2 27B up to 2,048, Aya Expanse 32B up to 4,000 tokens.

Which can read images, PDFs, audio or video?

Qwen2.5-Coder-32B-Instruct accepts text; Gemma 2 27B accepts text; Aya Expanse 32B accepts text. They handle the same number of input types.

Are any of these open source?

Yes, all three publish their weights (CC-BY-NC-4.0), so you can self-host them.

Which is newer?

Qwen2.5-Coder-32B-Instruct is the newest, released Nov 12, 2024. Aya Expanse 32B came out Oct 24, 2024; Gemma 2 27B came out Jul 13, 2024. Knowledge cutoff: Gemma 2 27B Jun 30, 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.

05 — Keep comparing

Related comparisons