DeepSeek V4 Flash Vision Exp vs Mistral Small 3Which Is Better in 2026?
DeepSeek V4 Flash Vision Exp vs Mistral Small 3: which should you choose in 2026?
DeepSeek V4 Flash Vision Exp (by DeepSeek) and Mistral Small 3 (by Mistral AI) are compared below. Here is how they stack up on benchmarks, price, and capabilities, and which one to pick in 2026.
There are not enough shared, protocol-compatible benchmark results to declare a performance leader.
At least one model uses context-dependent token-pricing tiers, so the published base rates do not support an unconditional blended price comparison.
DeepSeek V4 Flash Vision Exp has the larger context window (1,048,576 tokens vs 32,768 tokens).
Choose DeepSeek V4 Flash Vision Exp if…
- • you work with longer documents, transcripts, or codebases
- • you need a model with explicit reasoning support
- • you need image inputs
Choose Mistral Small 3 if…
- • your own prompt tests favor its output; shared comparable evidence does not identify a unique advantage
The benchmark count includes only results measured with a matching benchmark version and protocol. Arena scores are shown separately. Missing, preliminary, and incompatible data is not treated as a controlled win. Published point-score comparisons are labeled separately when protocol details are incomplete. For text-output models, the verdict also compares token pricing and context windows.
Performance benchmarks
Every value links to its source. A dash means that no reviewed result is available for that exact model and protocol.
| Benchmark | DeepSeek V4 Flash Vision Exp | Mistral Small 3 |
|---|---|---|
A 657-task benchmark of multi-step work across simulated SaaS applications in six business domains. The Artificial Analysis protocol reports a guardrail-aware score and is distinct from both the public Zapier split and the unrelated dynamic AutoBench framework. Guardrail-aware score | — | — |
A benchmark of difficult, verifiable information-seeking questions designed to measure an agent's ability to locate hard-to-find facts through web browsing. Accuracy | — | — |
A verified computer-use benchmark in which multimodal agents operate desktop applications and are graded from the resulting environment state. Mean task reward | — | — |
A human-validated subset of real GitHub issues used to measure whether a coding agent can produce repository patches that resolve the associated tests. Resolved | — | — |
Version 2.1 of the benchmark for completing realistic tasks in terminal environments. Harness, resource limits, and attempt count are part of the protocol. Mean task success | — | — |
A dynamic LLM evaluation framework in which models generate questions, answer them, and participate in reciprocal peer assessment. AutoBench is distinct from Zapier's AutomationBench. Weighted peer-assessment score | — | — |
The highest-quality subset of Graduate-Level Google-Proof Q&A, designed to test expert-level scientific reasoning in biology, physics, and chemistry. Accuracy | — | — |
A 2,500-question expert-level benchmark spanning dozens of academic fields. Tool-assisted and no-tools results are separate protocols and must not be merged. Accuracy | — | — |
| Arena preference scores | ||
Human preference score | — | 1274 ±6 |
Benchmark sources
Reviewed evidence last updated 2026-08-09. Arena data last refreshed Aug 25, 2026.
Pricing, capabilities, and model facts
| Feature | DeepSeek V4 Flash Vision Exp | Mistral Small 3 |
|---|---|---|
| Context & model facts | ||
| Developer | DeepSeek | Mistral AI |
| API provider | DeepSeek | Mistral |
| Input context | 1,048,576 tokens | 32,768 tokens |
| Maximum output | 384,000 tokens | 16,384 tokens |
| Released | — | — |
| Added to Writingmate | Aug 21, 2026 | Jan 30, 2025 |
| License | Not available | Not available |
| Knowledge cutoff | — | 2023-10-31 |
| Capabilities | ||
| Inputs | Text, Image | Text |
| Outputs | Text | Text |
| Provider endpoint accepts tool parameters | Yes | No |
| Reasoning | Yes | No |
| Vision | Yes | No |
| Image Generation | No | No |
| Video Generation | No | No |
| API pricing | ||
| Base input (per 1M tokens) | $0.44 | $0.05 |
| Base output (per 1M tokens) | $1.32 | $0.08 |
| Higher-context pricing tiers | Base rate only | Base rate only |
| Price-comparison caveat | At least one model changes token rates above a prompt-token threshold. Base rates are shown, but an unconditional blended price ratio would not be like-for-like. | |
| API performance | ||
| p95 latency | Not measured | Not measured |
| Output throughput | Not measured | Not measured |
| Writingmate shows API performance only when both models have enough observations from the same measurement window, prompt profile, and provider. Third-party latency values are not copied into this table. | ||
Data sources
- Writingmate model catalog (pricing, limits, and availability)
Catalog data last updated Aug 21, 2026.
Why Pay for Multiple Subscriptions?
Comparing DeepSeek V4 Flash Vision Exp from DeepSeek with Mistral Small 3 from Mistral AI? Instead of managing separate API keys and subscriptions, get both with Writingmate.
| Plan | Price | DeepSeek V4 Flash Vision Exp | Mistral Small 3 | AI Images | AI Video |
|---|---|---|---|---|---|
Writingmate Pro Most popular | $20/mo | Included | Included | Nano Banana Pro, FLUX.2, DALL-E & more | Sora 2, VEO 3.1 |
Writingmate Ultimate Power users | $60/mo | Included | Included | Nano Banana Pro, FLUX.2, DALL-E & more | Sora 2, VEO 3.1 |
DeepSeek V4 Flash Vision Exp vs Mistral Small 3 FAQ
Which is better, DeepSeek V4 Flash Vision Exp or Mistral Small 3?
There are not enough shared, protocol-compatible benchmark results to declare a performance leader. At least one model uses context-dependent token-pricing tiers, so the published base rates do not support an unconditional blended price comparison. DeepSeek V4 Flash Vision Exp has the larger context window (1,048,576 tokens vs 32,768 tokens).
Which model is cheaper to use through an API?
At least one model uses context-dependent token-pricing tiers, so the published base rates do not support an unconditional blended price comparison.
Which model supports more context?
DeepSeek V4 Flash Vision Exp has the larger context window (1,048,576 tokens vs 32,768 tokens).
Can I switch between DeepSeek V4 Flash Vision Exp and Mistral Small 3?
Yes. Use the model selector on this page to open any current Writingmate model comparison. You can also run the same prompt with both models in Writingmate.
Related comparisons
More DeepSeek V4 Flash Vision Exp comparisons
Muse Spark 1.2 Contributor
Meta
Muse Spark 1.2 contributor tier is a reasoning model from Meta designed for developers who want to start building at an even lower cost.
Ox Alpha
Stealth
Ox Alpha is a reasoning model designed for coding, sustained agentic work, and production workloads.
Qwen3.8 27B
Qwen
Qwen3.8 27B is an open-weight dense vision-language model from Qwen.
Gemini 3.7 Flash
Gemini 3.7 Flash is a multimodal model from Google for fast agentic workflows, coding, and complex multi-step reasoning.
Seed 2.1 Turbo
ByteDance
Seed 2.1 Turbo is a multimodal model from ByteDance Seed for coding and long-horizon agent workflows.
Seed-2.0-Code
ByteDance
Seed 2.0 Code is a model from ByteDance Seed optimized for agentic coding.
More Mistral Small 3 comparisons
Muse Spark 1.2 Contributor
Meta
Muse Spark 1.2 contributor tier is a reasoning model from Meta designed for developers who want to start building at an even lower cost.
Ox Alpha
Stealth
Ox Alpha is a reasoning model designed for coding, sustained agentic work, and production workloads.
Hy-MT2-1.8B
Tencent
Hy-MT2-1.8B is a compact 1.8B-parameter translation model from Tencent.
Hy-MT2-30B-A3B
Tencent
Hy-MT2-30B-A3B is Tencent's flagship translation model in the Hy-MT2 family.
Hy-MT2-7B
Tencent
Hy-MT2-7B is a 7B-parameter translation model from Tencent.
GLM 5.3
Z.AI
GLM-5.3 is a large-scale reasoning model from Z.ai, built for complex software engineering and long-horizon agent tasks.