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Gemma 4 26B A4B vs Qwen3 VL 30B (Fireworks): API Cost Comparison

Compare the API pricing, context windows, features, and real-world cost projections for Gemma 4 26B A4B (Google) and Qwen3 VL 30B (Fireworks) (Fireworks AI). Use the interactive calculator below to compute your exact monthly cost based on your token usage and request volume.

Prices verified Apr 5, 2026

Interactive Cost Calculator

GoogleGemma 4 26B A4B Fireworks AIQwen3 VL 30B (Fireworks)

Fills in typical token counts for a workload type

Tokens in each prompt sent to the model

Tokens generated in each response

Total API calls per month

Showing costs for 2 models. Cheapest: Gemma 4 26B A4B at $3.30/month.

Cheapest: Gemma 4 26B A4B at $3.30/mo — save 26.7% vs Qwen3 VL 30B (Fireworks)
Alert
BestGemma 4 26B A4B
Google$3.30$0.000330$1.30$2.0026.7%Alerts coming soon
Qwen3 VL 30B (Fireworks)
Fireworks AI$4.50$0.000450$1.50$3.00Alerts coming soon

Monthly Cost Comparison

Price Comparison at a Glance

All prices are in USD per 1 million tokens ($/M tokens). Lower is cheaper.

Pricing TypeGemma 4 26B A4B Qwen3 VL 30B (Fireworks)Cheaper
Input (standard)$0.13/M$0.15/MGemma 4 26B A4B
Output$0.40/M$0.60/MGemma 4 26B A4B
Cached inputN/A$0.08/M
Batch inputN/A$0.08/M
Batch outputN/A$0.30/M

Prices last verified: 2026-03-10 – 2026-04-05

Cost Breakdown by Usage Volume

Estimated monthly costs at different request volumes, assuming 1,000 input tokens and 500 output tokens per request. Adjust in the calculator above for your specific use case.

VolumeGemma 4 26B A4B MonthlyQwen3 VL 30B (Fireworks)MonthlyGemma 4 26B A4B Per requestQwen3 VL 30B (Fireworks)Per request
1K requests/mo$0.33$0.45$0.000330$0.000450
10K requests/mo$3.30$4.50$0.000330$0.000450
100K requests/mo$33.00$45.00$0.000330$0.000450
1M requests/mo$330.00$450.00$0.000330$0.000450

Green values indicate the lower-cost option at each volume tier. Cost per request is calculated at 1,000 input + 500 output tokens using standard (non-batch, non-cached) pricing.

Price History

Input price per 1M tokens

When to Choose Gemma 4 26B A4B

by Google

  • General chatbot

Input / 1M tokens

$0.13/M

Output / 1M tokens

$0.40/M

Context window

262,144

Tier

budget

When to Choose Qwen3 VL 30B (Fireworks)

by Fireworks AI

  • Document summarization
  • General chatbot

Input / 1M tokens

$0.15/M

Output / 1M tokens

$0.60/M

Context window

262,144

Tier

mid

Key Differences Beyond Price

Cost is only one factor in choosing an AI model. Context window size, rate limits, supported features, and latency all affect whether a model fits your use case.

CapabilityGemma 4 26B A4B Qwen3 VL 30B (Fireworks)
Context window262,144 tokens262,144 tokens
Max output tokens262,144 tokens8,192 tokens
Performance tierBudgetMid
Vision / image inputYesYes
Function callingYesYes
JSON modeYesYes
Prompt cachingNoYes
Batch API (50% discount)NoYes
Extended reasoningYesNo
Fine-tuningNoNo

Qwen3 VL 30B (Fireworks) notes

Fireworks serverless pricing. Vision/multimodal capable. Cached input 50% discount.

Frequently Asked Questions

Is Gemma 4 26B A4B cheaper than Qwen3 VL 30B (Fireworks)?

At standard usage (1,000 input tokens, 500 output tokens, 100,000 requests/month), Gemma 4 26B A4B costs $33.00/month versus $45.00/month for Qwen3 VL 30B (Fireworks) — a 27% saving. Your actual savings will vary based on your token profile; output-heavy workloads amplify differences in output pricing.

Which model has a larger context window, Gemma 4 26B A4B or Qwen3 VL 30B (Fireworks)?

Both Gemma 4 26B A4B and Qwen3 VL 30B (Fireworks) have the same context window: 262,144 tokens.

Do Gemma 4 26B A4B and Qwen3 VL 30B (Fireworks) support the Batch API?

Qwen3 VL 30B (Fireworks) supports the Batch API (50% discount for async processing), while Gemma 4 26B A4B does not. If your workload tolerates up to 24-hour latency, routing to Qwen3 VL 30B (Fireworks) with batch pricing could significantly cut costs versus Gemma 4 26B A4B 's standard rate.

Which model offers better prompt caching?

Qwen3 VL 30B (Fireworks) supports prompt caching at $0.08/M for cached input, while Gemma 4 26B A4B does not offer prompt caching. For RAG applications or chatbots with large, repeated context, Qwen3 VL 30B (Fireworks)'s caching capability can substantially reduce effective costs.

What are the best use cases for Gemma 4 26B A4B vs Qwen3 VL 30B (Fireworks)?

Both models are well-suited for General chatbot. Gemma 4 26B A4B is particularly strong for overlapping tasks. Qwen3 VL 30B (Fireworks) is favored for Document summarization. At the same quality level, the lower-cost model is usually preferable; use this page's calculator to compare total monthly spend at your volume.

What is the cost per request for Gemma 4 26B A4B vs Qwen3 VL 30B (Fireworks)?

At 1,000 input tokens and 500 output tokens per request — a typical conversational workload — Gemma 4 26B A4B costs $0.000330 per request and Qwen3 VL 30B (Fireworks) costs $0.000450 per request. At 100,000 requests/month, that translates to $33.00 and $45.00 respectively. Use the interactive calculator to adjust these parameters for your actual workload.

Gemma 4 26B A4B vs Qwen3 VL 30B (Fireworks): Summary

When comparing Gemma 4 26B A4B and Qwen3 VL 30B (Fireworks) for API cost, the right choice depends on your workload's token profile, required features, and tolerance for latency. Gemma 4 26B A4B offers lower total cost at standard usage volumes (1,000 input + 500 output tokens per request at 100,000 requests/month) at $33.00/month, compared to $45.00/month for Qwen3 VL 30B (Fireworks).

Both models are priced in USD per million tokens, the standard unit across all major AI API providers. Gemma 4 26B A4B charges $0.13/M for input tokens and $0.40/M for output tokens. Qwen3 VL 30B (Fireworks) charges $0.15/M input and $0.60/M output. If your workload is output-heavy (more tokens generated than consumed as input), the model with the lower output price compounds cost savings significantly at scale.

Prompt caching is supported by Qwen3 VL 30B (Fireworks) but not Gemma 4 26B A4B . For workloads with large, repeated system prompts or document context — such as RAG pipelines or multi-turn conversations with a fixed knowledge base — prompt caching can reduce effective input costs by 60–90%, which may change the cost ranking between these two models at your specific usage pattern.

Context window capacity differs between the two: Both models support 262,144 tokens per request. A larger context window is essential for document summarization, large codebase analysis, and multi-document retrieval-augmented generation (RAG) applications.

Use the interactive calculator at the top of this page to enter your actual token usage and monthly request volume for a precise cost comparison tailored to your workload. Adjust for batch API discounts and prompt caching to find the most cost-effective option for your specific deployment.

Explore other model comparisons from the same providers or performance tiers.

Related Provider Pages

View complete pricing tables and model lineups for the providers behind these models.

Relevant Use Cases

See cost recommendations for workloads where Gemma 4 26B A4B or Qwen3 VL 30B (Fireworks) is recommended.