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DeepSeek-V4-Flash-0423 vs Gemma 4 31B

DeepSeek-V4-Flash-0423 and Gemma 4 31B are closely matched at 36.6 and 33.4 on the LLM Stats Score. DeepSeek-V4-Flash-0423 is 1.5x cheaper per token.

DeepSeek · Google · Updated for 2026

Which is better?

DeepSeek-V4-Flash-0423 and Gemma 4 31B are closely matched on the overall LLM Stats Score at 36.6 and 33.4.

In the 3 individual benchmarks reported for both models, DeepSeek-V4-Flash-0423 wins 3; this is a narrower head-to-head signal than the composite indexes.

On price, DeepSeek-V4-Flash-0423 is roughly 1.5x cheaper per token on a blended 3:1 input/output basis, which adds up quickly at production volume.

DeepSeek-V4-Flash-0423 also accepts a larger context window (1,048,576 input tokens), making it the stronger choice for long documents and large codebases.

Based on current LLM Stats indexes, shared benchmarks, pricing, and model metadata for 2026.

Choose DeepSeek-V4-Flash-0423

  • you value its reported benchmark strengths — it wins 3 of 3 exact shared results
  • cost matters — it's about 1.5x cheaper per token
  • you process long inputs — it offers a 1,048,576 token context window
  • you want the most recent training data — it shipped Apr 2026

Choose Gemma 4 31B

  • you want predictable pricing at $0.13/M input and $0.38/M output

At a glance

The differences that matter most.

Core performance indexes
36.6
#67
33.4
#87
37.6
#59
34.0
#81
17.3
#68
14.3
#78
Cost, coverage & limits
Benchmark wins
3 of 3
0 of 3
Input price
$0.10 / M
$0.13 / M
Output price
$0.20 / M
$0.38 / M
Context window
1,048,576
262,144

Capability indexes

Additional strengths measured across groups of related public benchmarks

2 shared
Index
DeepSeek-V4-Flash-0423
Gemma 4 31B
37.8#26
29.3#78
3.1#94
17.4#37
Conservative TrueSkill rating · higher is betterHow scores work

Individual benchmarks

19 reported for DeepSeek-V4-Flash-0423 · 12 for Gemma 4 31B

3 shared

DeepSeek-V4-Flash-0423 outperforms in 3 benchmarks (GPQA, Humanity's Last Exam, MMLU-Pro), while Gemma 4 31B is better at 0 benchmarks.

DeepSeek-V4-Flash-0423 significantly outperforms across most benchmarks.

Fri Aug 28 2026 • llm-stats.com

Human preference

Blind head-to-head votes and playground preference scores

Pricing Analysis

Price comparison per million tokens

DeepSeek-V4-Flash-0423 costs less

For input processing, DeepSeek-V4-Flash-0423 ($0.10/1M tokens) is 1.3x cheaper than Gemma 4 31B ($0.13/1M tokens).

For output processing, DeepSeek-V4-Flash-0423 ($0.20/1M tokens) is 1.9x cheaper than Gemma 4 31B ($0.38/1M tokens).

In conclusion, Gemma 4 31B is more expensive than DeepSeek-V4-Flash-0423.*

* Using a 3:1 ratio of input to output tokens

Lowest available price from all providers
Fri Aug 28 2026 • llm-stats.com
DeepSeek
DeepSeek-V4-Flash-0423
Input tokens$0.10
Output tokens$0.20
Best providerDeepinfra
Google
Gemma 4 31B
Input tokens$0.13
Output tokens$0.38
Best providerDeepinfra
Notice missing or incorrect data?Start an Issue

Model Size

Parameter count comparison

253.3B diff

DeepSeek-V4-Flash-0423 has 253.3B more parameters than Gemma 4 31B, making it 825.1% larger.

DeepSeek
DeepSeek-V4-Flash-0423
284.0Bparameters
Google
Gemma 4 31B
30.7Bparameters
284.0B
DeepSeek-V4-Flash-0423
30.7B
Gemma 4 31B

Context Window

Maximum input and output token capacity

DeepSeek-V4-Flash-0423 accepts 1,048,576 input tokens compared to Gemma 4 31B's 262,144 tokens. Gemma 4 31B can generate longer responses up to 131,072 tokens, while DeepSeek-V4-Flash-0423 is limited to 65,536 tokens.

DeepSeek
DeepSeek-V4-Flash-0423
Input1,048,576 tokens
Output65,536 tokens
Google
Gemma 4 31B
Input262,144 tokens
Output131,072 tokens
Fri Aug 28 2026 • llm-stats.com

Input capabilities

Documented input modalities across available providers

Gemma 4 31B supports multimodal inputs, whereas DeepSeek-V4-Flash-0423 does not.

Gemma 4 31B can handle both text and other forms of data like images, making it suitable for multimodal applications.

DeepSeek-V4-Flash-0423

Text
Images
Audio
Video

Gemma 4 31B

Text
Images
Audio
Video

License

Usage and distribution terms

DeepSeek-V4-Flash-0423 is licensed under MIT, while Gemma 4 31B uses Apache 2.0.

License differences may affect how you can use these models in commercial or open-source projects.

DeepSeek-V4-Flash-0423

MIT

Open weights

Gemma 4 31B

Apache 2.0

Open weights

Release Timeline

When each model was launched

DeepSeek-V4-Flash-0423 was released on 2026-04-23, while Gemma 4 31B was released on 2026-04-02.

DeepSeek-V4-Flash-0423 is 1 month newer than Gemma 4 31B.

DeepSeek-V4-Flash-0423

Apr 23, 2026

4 months ago

3w newer
Gemma 4 31B

Apr 2, 2026

4 months ago

Knowledge Cutoff

When training data ends

Gemma 4 31B has a documented knowledge cutoff of 2025-01-01, while DeepSeek-V4-Flash-0423's cutoff date is not specified.

We can confirm Gemma 4 31B's training data extends to 2025-01-01, but cannot make a direct comparison without DeepSeek-V4-Flash-0423's cutoff date.

DeepSeek-V4-Flash-0423

Gemma 4 31B

Jan 2025

Provider Availability

DeepSeek-V4-Flash-0423 is available from DeepInfra, Novita. Gemma 4 31B is available from DeepInfra, FriendliAI, Novita, Together.

DeepSeek-V4-Flash-0423

deepinfra logo
Deepinfra
Input Price:Input: $0.10/1MOutput Price:Output: $0.20/1M
novita logo
Novita
Input Price:Input: $0.14/1MOutput Price:Output: $0.28/1M

Gemma 4 31B

deepinfra logo
Deepinfra
Input Price:Input: $0.13/1MOutput Price:Output: $0.38/1M
friendli logo
FriendliAI
Input Price:Input: $0.14/1MOutput Price:Output: $0.40/1M
novita logo
Novita
Input Price:Input: $0.14/1MOutput Price:Output: $0.40/1M
together logo
Together
Input Price:Input: $0.39/1MOutput Price:Output: $0.97/1M
* Prices shown are per million tokens

Outputs Comparison

Notice missing or incorrect data?Start an Issue discussion

Judge for yourself.

Run your own prompts against DeepSeek-V4-Flash-0423 and Gemma 4 31B side-by-side, then vote on the output you prefer.

DeepSeek-V4-Flash-0423
✓ Preferred
Gemma 4 31B
Open in Playground

FAQ

Common questions about DeepSeek-V4-Flash-0423 vs Gemma 4 31B.

Which is better, DeepSeek-V4-Flash-0423 or Gemma 4 31B?

DeepSeek-V4-Flash-0423 and Gemma 4 31B are closely matched on the LLM Stats Score at 36.6 and 33.4. DeepSeek-V4-Flash-0423 is made by DeepSeek and Gemma 4 31B is made by Google. The best choice depends on your use case — compare their capability indexes, individual benchmarks, pricing, and limits above.

How does DeepSeek-V4-Flash-0423 compare to Gemma 4 31B in benchmarks?

DeepSeek-V4-Flash-0423 scores CodeForces: 93.9%, HMMT Feb 26: 91.9%, LiveCodeBench: 88.4%, GPQA: 87.4%, MMLU-Pro: 86.4%. Gemma 4 31B scores AIME 2026: 89.2%, MMMLU: 88.4%, t2-bench: 86.4%, MathVision: 85.6%, MMLU-Pro: 85.2%.

Is DeepSeek-V4-Flash-0423 cheaper than Gemma 4 31B?

DeepSeek-V4-Flash-0423 is 1.3x cheaper for input tokens. DeepSeek-V4-Flash-0423 costs $0.10/M input and $0.20/M output via deepinfra. Gemma 4 31B costs $0.13/M input and $0.38/M output via deepinfra.

What are the context window sizes for DeepSeek-V4-Flash-0423 and Gemma 4 31B?

DeepSeek-V4-Flash-0423 supports 1.0M tokens and Gemma 4 31B supports 262K tokens. A larger context window lets you process longer documents, conversations, or codebases in a single request.

What are the main differences between DeepSeek-V4-Flash-0423 and Gemma 4 31B?

Key differences include LLM Stats Score (36.6 vs 33.4), context window (1.0M vs 262K), input pricing ($0.10 vs $0.13/M), multimodal support (no vs yes), licensing (MIT vs Apache 2.0). See the full comparison above for benchmark-by-benchmark results.

Who makes DeepSeek-V4-Flash-0423 and Gemma 4 31B?

DeepSeek-V4-Flash-0423 is developed by DeepSeek and Gemma 4 31B is developed by Google.