ZMIME
Comparison · 3 models · Updated Oct 4, 2026

GPT OSS 120B vs Gemini 2.5 Flash-Lite vs Qwen3 235B-A22B Instruct 2507

Gemini 2.5 Flash-Lite comes out ahead, 71 to 61 and 58 on our weighted score, and it is the cheaper option too.

  1. OpenAI

    GPT OSS 120B

    Released Aug 5, 2025

    61/100
    • ECI140.0
    • Price$0.15 / $0.60
    • Context131K
  2. Our pick

    Google

    Gemini 2.5 Flash-Lite

    Released Jun 17, 2025

    71/100
    • ECI133.9
    • Price$0.10 / $0.40
    • Context1.05M
  3. Alibaba (Qwen)

    Qwen3 235B-A22B Instruct 2507

    Released Jul 21, 2025

    58/100
    • ECI138.9
    • Price$0.15 / $0.75
    • Context262K
01 — Verdict

Gemini 2.5 Flash-Lite is our pick

Gemini 2.5 Flash-Lite is the better all-round choice, scoring 71/100 against GPT OSS 120B (61) and Qwen3 235B-A22B Instruct 2507 (58). It leads on price, inputs & features and context window. The score weighs capability 50%, price 25%, inputs & features 15%, context window 10%.

  • CapabilityGPT OSS 120BCapabilities Index (ECI): GPT OSS 120B 140.0 · Qwen3 235B-A22B Instruct 2507 138.9 · Gemini 2.5 Flash-Lite 133.9
  • Lowest priceGemini 2.5 Flash-LiteGemini 2.5 Flash-Lite $0.175 · GPT OSS 120B $0.263 · Qwen3 235B-A22B Instruct 2507 $0.30 per 1M tokens (3:1 blend)
  • Longest contextGemini 2.5 Flash-LiteGemini 2.5 Flash-Lite 1,048,576 · Qwen3 235B-A22B Instruct 2507 262,144 · GPT OSS 120B 131,072 tokens
  • Widest inputsGemini 2.5 Flash-LiteGPT OSS 120B: Text · Gemini 2.5 Flash-Lite: Text, Images, PDFs, Audio, Video · Qwen3 235B-A22B Instruct 2507: Text
  • Self-hostingGPT OSS 120B and Qwen3 235B-A22B Instruct 2507Publishes downloadable weights (Apache 2.0)
How the score is built
MeasureWeightGPT OSS 120BGemini 2.5 Flash-LiteQwen3 235B-A22B Instruct 2507
CapabilityCapabilities Index (ECI)50%655864
Price25%778675
Inputs & features15%4510025
Context window10%246137
Overall100%61/10071/10058/100
02 — Side by side

Every spec in one table

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

GPT OSS 120B vs Gemini 2.5 Flash-Lite vs Qwen3 235B-A22B Instruct 2507 specifications side by side
SpecificationGPT OSS 120BOpenAIGemini 2.5 Flash-LiteGoogleQwen3 235B-A22B Instruct 2507Alibaba (Qwen)
Capability
Capabilities Index (ECI)140.0 (best)133.9138.9
ECI rank#99 of 148 (best)#118 of 148#105 of 148
GPQA DiamondGraduate-level science questions75.8%——
OTIS Mock AIME 2024–2025Competition mathematics88.9%——
Price per million tokens
Input$0.15$0.10 (best)$0.15
Output$0.60$0.40 (best)$0.75
Cached input—$0.01—
Blended (3:1)$0.263$0.175 (best)$0.30
Long-context rateSame rateSame rateSame rate
Price sourceMedian of 36 providersOfficial Google APIMedian of 11 providers
Limits
Context window131,072 tokens1,048,576 tokens (best)262,144 tokens
Max output32,768 tokens65,536 tokens (best)16,384 tokens
Inputs and features
TextYesYesYes
ImagesNoYesNo
PDFsNoYesNo
AudioNoYesNo
VideoNoYesNo
ReasoningYesYesNo
Tool callingYesYesYes
Structured outputYesYesNo
Availability
WeightsOpenProprietaryOpenApache 2.0
API model ID—gemini-2.5-flash-lite—
API providers39 (best)2011
ReleasedAug 5, 2025Jun 17, 2025Jul 21, 2025
Knowledge cutoff—Jan 2025—
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.

  • GPT OSS 120B$2.70
  • Gemini 2.5 Flash-Lite$1.80
  • Qwen3 235B-A22B Instruct 2507$3.00
04 — Questions

Which should you choose?

Which is better: GPT OSS 120B, Gemini 2.5 Flash-Lite or Qwen3 235B-A22B Instruct 2507?

Gemini 2.5 Flash-Lite is the better all-round choice, scoring 71/100 against GPT OSS 120B (61) and Qwen3 235B-A22B Instruct 2507 (58). It leads on price, inputs & features and context window. The score weighs capability 50%, price 25%, inputs & features 15%, context window 10%.

Which is cheaper, GPT OSS 120B, Gemini 2.5 Flash-Lite or Qwen3 235B-A22B Instruct 2507?

Gemini 2.5 Flash-Lite is cheaper at $0.10 input / $0.40 output per million tokens (official Google API price). GPT OSS 120B costs $0.15 input / $0.60 output per million tokens (median across 36 API providers); Qwen3 235B-A22B Instruct 2507 costs $0.15 input / $0.75 output per million tokens (median across 11 API providers). At a typical mix of three input tokens to one output token, that is $0.175 per million tokens for Gemini 2.5 Flash-Lite versus $0.263 for GPT OSS 120B (1.5× as much) and $0.30 for Qwen3 235B-A22B Instruct 2507 (1.7× as much).

Which scores higher on benchmarks?

GPT OSS 120B scores higher on the Capabilities Index (ECI): GPT OSS 120B 140.0 (#99 of 148), Qwen3 235B-A22B Instruct 2507 138.9 (#105 of 148) and Gemini 2.5 Flash-Lite 133.9 (#118 of 148). The confidence ranges of the top two overlap (135.3–142.3 vs 135.8–140.6), so treat the gap as small.

Which is better for coding?

There are no published SWE-bench Verified results for GPT OSS 120B, Gemini 2.5 Flash-Lite and Qwen3 235B-A22B Instruct 2507 yet, so there is no like-for-like coding score. On overall capability, GPT OSS 120B 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?

Gemini 2.5 Flash-Lite has the largest context window at 1,048,576 tokens, against 262,144 for Qwen3 235B-A22B Instruct 2507 and 131,072 for GPT OSS 120B. Maximum output per response: GPT OSS 120B up to 32,768, Gemini 2.5 Flash-Lite up to 65,536, Qwen3 235B-A22B Instruct 2507 up to 16,384 tokens.

Which can read images, PDFs, audio or video?

GPT OSS 120B accepts text; Gemini 2.5 Flash-Lite accepts text, images, PDFs, audio and video; Qwen3 235B-A22B Instruct 2507 accepts text. Gemini 2.5 Flash-Lite handles the widest range of inputs.

Are any of these open source?

GPT OSS 120B and Qwen3 235B-A22B Instruct 2507 publishes its weights (Apache 2.0) and can be self-hosted; Gemini 2.5 Flash-Lite is proprietary.

Which is newer?

GPT OSS 120B is the newest, released Aug 5, 2025. Qwen3 235B-A22B Instruct 2507 came out Jul 21, 2025; Gemini 2.5 Flash-Lite came out Jun 17, 2025. Knowledge cutoff: Gemini 2.5 Flash-Lite Jan 2025.

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.