ZMIME
Comparison · 3 models · Updated Oct 4, 2026

Qwen Turbo vs Claude Haiku 3.5 vs Gemma 3 12B IT

Too close to call on our weighted score (Gemma 3 12B IT 32, Qwen Turbo 31, Claude Haiku 3.5 30). The right pick depends on what you value most.

  1. Alibaba (Qwen)

    Qwen Turbo

    Released Nov 1, 2024

    31/100
    • ECI—
    • Price$0.05 / $0.20
    • Context1M
  2. Anthropic

    Claude Haiku 3.5

    Released Oct 22, 2024

    30/100
    • ECI127.2
    • Price—
    • Context200K
  3. Google

    Gemma 3 12B IT

    Released Mar 12, 2025

    32/100
    • ECI123.5
    • Price$0.05 / $0.15
    • Context131K
01 — Verdict

Too close to call

It is close. Our weighted score puts them within 1 points (Gemma 3 12B IT 32/100, Qwen Turbo 31/100, Claude Haiku 3.5 30/100), so choose by what matters most for your work: Gemma 3 12B IT for raw capability and Qwen Turbo for long inputs. The score weighs capability 67%, inputs & features 20%, context window 13%. Capability uses the average of shared benchmarks (GPQA Diamond and OTIS Mock AIME 2024–2025), because Qwen Turbo has no Capabilities Index score yet.

  • CapabilityGemma 3 12B ITShared benchmarks: Gemma 3 12B IT 28.1% · Qwen Turbo 24.0% · Claude Haiku 3.5 21.2%
  • Lowest priceGemma 3 12B ITGemma 3 12B IT $0.075 · Qwen Turbo $0.087 per 1M tokens (3:1 blend) · Claude Haiku 3.5 unpriced
  • Longest contextQwen TurboQwen Turbo 1,000,000 · Claude Haiku 3.5 200,000 · Gemma 3 12B IT 131,072 tokens
  • Widest inputsClaude Haiku 3.5Qwen Turbo: Text · Claude Haiku 3.5: Text, Images, PDFs · Gemma 3 12B IT: Text, Images
  • Self-hostingGemma 3 12B ITPublishes downloadable weights
How the score is built
MeasureWeightQwen TurboClaude Haiku 3.5Gemma 3 12B IT
CapabilityShared benchmarks67%242128
Inputs & features20%356050
Context window13%603224
Overall100%31/10030/10032/100

Left out because at least one model lacks the data: price. 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.

Qwen Turbo vs Claude Haiku 3.5 vs Gemma 3 12B IT specifications side by side
SpecificationQwen TurboAlibaba (Qwen)Claude Haiku 3.5AnthropicGemma 3 12B ITGoogle
Capability
Capabilities Index (ECI)—127.2 (best)123.5
ECI rank—#134 of 148 (best)#138 of 148
GPQA DiamondGraduate-level science questions41.8% (best)38.1%39.5%
OTIS Mock AIME 2024–2025Competition mathematics6.1%4.3%16.7% (best)
Price per million tokens
Input$0.05—$0.05
Output$0.20—$0.15 (best)
Cached input———
Blended (3:1)$0.087—$0.075 (best)
Long-context rateSame rate—Same rate
Price sourceOfficial Alibaba API—Median of 7 providers
Limits
Context window1,000,000 tokens (best)200,000 tokens131,072 tokens
Max output16,384 tokens8,192 tokens131,072 tokens (best)
Inputs and features
TextYesYesYes
ImagesNoYesYes
PDFsNoYesNo
AudioNoNoNo
VideoNoNoNo
ReasoningYesNoNo
Tool callingYesYesYes
Structured outputNoNoNo
Availability
WeightsProprietaryProprietaryOpen
API model IDqwen-turbo——
API providers3—7 (best)
ReleasedNov 1, 2024Oct 22, 2024Mar 12, 2025
Knowledge cutoffApr 2024Jul 31, 2024Aug 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.

  • Qwen Turbo$0.90
  • Claude Haiku 3.5—
  • Gemma 3 12B IT$0.80
04 — Questions

Which should you choose?

Which is better: Qwen Turbo, Claude Haiku 3.5 or Gemma 3 12B IT?

It is close. Our weighted score puts them within 1 points (Gemma 3 12B IT 32/100, Qwen Turbo 31/100, Claude Haiku 3.5 30/100), so choose by what matters most for your work: Gemma 3 12B IT for raw capability and Qwen Turbo for long inputs. The score weighs capability 67%, inputs & features 20%, context window 13%. Capability uses the average of shared benchmarks (GPQA Diamond and OTIS Mock AIME 2024–2025), because Qwen Turbo has no Capabilities Index score yet.

Which is cheaper, Qwen Turbo, Claude Haiku 3.5 or Gemma 3 12B IT?

Gemma 3 12B IT is cheaper at $0.05 input / $0.15 output per million tokens (median across 7 API providers). Qwen Turbo costs $0.05 input / $0.20 output per million tokens (official Alibaba API price). At a typical mix of three input tokens to one output token, that is $0.075 per million tokens for Gemma 3 12B IT versus $0.087 for Qwen Turbo (1.2× as much). Claude Haiku 3.5 has no published per-token price.

Which scores higher on benchmarks?

Not every model here has a Capabilities Index score, so we compare the average of shared benchmarks (GPQA Diamond and OTIS Mock AIME 2024–2025): Gemma 3 12B IT 28.1%, Qwen Turbo 24.0% and Claude Haiku 3.5 21.2%. On individual benchmarks: GPQA Diamond — Qwen Turbo 41.8%, Gemma 3 12B IT 39.5%, Claude Haiku 3.5 38.1%; OTIS Mock AIME 2024–2025 — Gemma 3 12B IT 16.7%, Qwen Turbo 6.1%, Claude Haiku 3.5 4.3%.

Which is better for coding?

There are no published SWE-bench Verified results for Qwen Turbo, Claude Haiku 3.5 and Gemma 3 12B IT yet, so there is no like-for-like coding score. On overall capability, Gemma 3 12B IT leads, which tends to carry over to coding, but test on your own codebase. All three support tool calling for agent workflows.

Which has the bigger context window?

Qwen Turbo has the largest context window at 1,000,000 tokens, against 200,000 for Claude Haiku 3.5 and 131,072 for Gemma 3 12B IT. Maximum output per response: Qwen Turbo up to 16,384, Claude Haiku 3.5 up to 8,192, Gemma 3 12B IT up to 131,072 tokens.

Which can read images, PDFs, audio or video?

Qwen Turbo accepts text; Claude Haiku 3.5 accepts text, images and PDFs; Gemma 3 12B IT accepts text and images. Claude Haiku 3.5 handles the widest range of inputs.

Are any of these open source?

Gemma 3 12B IT publishes its weights and can be self-hosted; Qwen Turbo and Claude Haiku 3.5 is proprietary.

Which is newer?

Gemma 3 12B IT is the newest, released Mar 12, 2025. Qwen Turbo came out Nov 1, 2024; Claude Haiku 3.5 came out Oct 22, 2024. Knowledge cutoff: Qwen Turbo Apr 2024, Claude Haiku 3.5 Jul 31, 2024, Gemma 3 12B IT Aug 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 Oct 4, 2026.