AI is no longer a "bonus" feature inside creative tools: in 2026, it is the tool. Editing a video, producing a slide deck, generating a voice-over, running a model on your own machine — every category has its winners, its licensing traps and its quiet price hikes. Here is the cross-category comparison, figures verified on July 3, 2026, with a top 3 per category and a one-page state-of-the-art recap at the end.
Prices and licences verified on July 3, 2026, against official pages whenever possible. SaaS pricing moves fast (CapCut doubled its annual plan in early 2026, Descript changed its model in September 2025): double-check before buying. Benchmarks self-reported by vendors are flagged with an asterisk (*).
The recap card at a glance — details and justifications below.
Video editing: AI makes the first cut
The market has split into two families. On one side, traditional NLEs that absorbed AI (DaVinci Resolve 21, Premiere Pro 26.2); on the other, AI-native editors where AI is the interface itself (Descript and its Underlord agent, CapCut Auto-Edit, Opus Clip). Most teams keep one of each. The other strong 2026 signal: AI-credit monetisation is now everywhere… except at Blackmagic, which holds out with its perpetual licence.
| Tool | The AI, in short | Price (07/2026) | Platforms |
|---|---|---|---|
| DaVinci Resolve 21 | IntelliScript (timeline from a script), SmartSwitch multicam, IntelliSearch | Free · Studio $295 one-time | Windows, macOS, Linux |
| Premiere Pro 26.2 | Generative Extend (Firefly), semantic search, Enhance Speech | from $22.99/mo + Firefly credits | Windows, macOS |
| CapCut "2026 AI Suite" | Auto-Edit, captions in 130+ languages, AI avatars | Free · Pro $19.99/mo | Windows, macOS, mobile, web |
| Descript | Text-based editing + the Underlord agent | Free · Creator $24/mo (annual) | Windows, macOS, web |
| Runway (Gen-4.5, Aleph) | Video generation + prompt-based editing of existing footage | Free · from $12/mo (credits) | Web (so Linux works) |
| Filmora 15 | AI Mate + built-in Sora 2, Veo 3.1 and Kling | from $49.99/yr · $79.99 perpetual | Windows, macOS |
Three profiles, three picks. The professional editor should take DaVinci Resolve Studio 21: AI at every post-production stage, reference-grade colour tools, the only major NLE on Linux — and $295 once, where the Adobe equation (subscription + credits) exceeds that in year one. The short-form creator stays on CapCut: the shortest path from footage to TikTok/Reels, at the cost of credit dependence and a brutal price hike (the annual Pro plan jumped from about $78 to $179.99). The podcaster picks Descript: editing video by fixing the transcript is still the most productive idea of the decade, and Underlord (best-take selection, social clips, Studio Sound cleanup) makes it a genuine agentic co-editor.
- DaVinci Resolve Studio 21 — the pro pick: $295 for life, AI everywhere, alone on Linux.
- CapCut Pro — the creator pick: fastest social pipeline, generous free tier.
- Descript — the podcast/talking-head pick: text-based editing + the Underlord agent.
Runway (Aleph) is a separate case: not an editing bench but the reference for generative editing — add it to one of the three, not instead of them.
Presentations: from prompt to PPTX… everywhere, Linux included
Generating a full deck from a prompt is now table stakes — the real 2026 topic is portability: what is a deck worth if it won't open on your client's machine? Two facts structure the category. First, every serious SaaS exports PPTX, with varying fidelity (fonts, gradients, animations). Second, no AI SaaS exports ODP natively: the OpenDocument format requires going through Google Slides (File → Download → ODP) or through LibreOffice/OnlyOffice, which write it natively.
Tome, the generative-deck pioneer (a claimed 20M users), shut down on April 30, 2025 — decks that hadn't been exported were permanently deleted. The moral: whatever SaaS you pick, export what matters to PPTX/PDF.
| Tool | Type | AI generation | Exports | Price (07/2026) |
|---|---|---|---|---|
| Gamma | SaaS (web) | full deck in ~30 s | PPTX, PDF, PNG, Google Slides — from the free plan | Free (400 credits) · Plus $9 · Pro ~$18–25/mo |
| Plus AI | Slides/PowerPoint add-in | inside the host app | native PPTX; ODP via Google Slides | from $10/mo |
| Presenton | open source (Apache 2.0), Docker/desktop | prompt → deck, your choice of LLM (local Ollama, OpenAI, Claude…) | editable PPTX, PDF | Free self-hosted |
| Presentations.ai | SaaS (web) | business decks | high-fidelity PPTX, PDF | Free · Pro $20/mo |
| Beautiful.ai | SaaS (web) | Smart Slides (auto design) | PPTX, PDF — no free plan | from $12/mo (annual) |
| OnlyOffice / LibreOffice | free software, desktop | in-editor assistants (AI plugin, Ollama possible) | native PPTX + ODP + PDF | Free |
Gamma remains the best all-rounder: the most polished first draft on the market, exports available even on the free tier — but converting its web-native "cards" to classic 16
needs cleanup, and the 400 free credits never renew. For a company that lives in PowerPoint, Plus AI wins by construction: it works inside Google Slides or PowerPoint, so the output file is natively clean — and it's the only near-direct path to ODP. On the open-source side, Presenton is the genuine surprise: Apache 2.0, desktop apps for Windows/macOS/Linux or Docker, fully editable PPTX, and any LLM you like — including 100% local via Ollama for full confidentiality. Finally, if native ODP is non-negotiable, OnlyOffice and LibreOffice Impress remain the only ones writing it directly, with in-editor AI assistants (OnlyOffice's plugin accepts a local model) rather than full deck generation.- Gamma — the all-rounder: best first draft, PPTX/PDF exports from the free tier.
- Plus AI — the enterprise pick: native PPTX with zero conversion, ODP path via Google Slides, $10/mo.
- Presenton — the open-source pick: Apache 2.0, Linux/macOS/Windows, local LLM support, editable PPTX.
Text-to-speech: premium cloud vs. free local
Two worlds coexist: cloud APIs, which dominate on expressiveness, and open-source models that have become genuinely production-ready locally — they all run effortlessly on a recent computer; the podium's largest model weighs 1.7 billion parameters. No four-figure GPU required.
Paid (APIs)
| Service | Edge | French | Price ≈ / M characters |
|---|---|---|---|
| ElevenLabs (Eleven v3) | 70+ languages, emotional "audio tags", cloning | excellent | $50–100 |
| OpenAI gpt-4o-mini-tts | prompt steering, floor pricing (~$0.015/min) | decent | $12–15 |
| Cartesia Sonic-3.5 | 40–90 ms latency (real-time voice agents) | native (42 languages) | ~$38 |
| Hume Octave 2 | contextual emotion (the text is "understood") | yes (11+ languages) | ~$50 |
Local (open source)
Check the licence of the weights, not the code. F5-TTS: MIT code but CC-BY-NC weights → no commercial use. Fish Speech / OpenAudio S1-mini: CC-BY-NC-SA. XTTS-v2: non-commercial licence and Coqui shut down in 2024 — there is nobody left to sell you a licence. All three are excellent, and all three are off-limits for a product.
| Model | Size | Licence | French | Voice cloning |
|---|---|---|---|---|
| Chatterbox Multilingual V3 (Resemble) | 0.5B | MIT | 23 languages, FR included | from 5 s of audio |
| Qwen3-TTS 1.7B (Alibaba, 01/2026) | 1.7B (MLX ports) | Apache 2.0 | native (10 languages) | 3 s + prompt-based "voice design" |
| Kokoro-82M | 82M (~350 MB!) | Apache 2.0 | 1 voice only, B− quality | no |
| Orpheus 3B | 3B (GGUF) | Apache 2.0 | FR as a research release | yes |
| NeuTTS Air (Neuphonic) | 748M | Apache 2.0 | yes (EN stronger) | 3 s |
Chatterbox V3 ticks every box: MIT (the only top-tier model truly free for commercial use), 23 languages, zero-shot cloning from 5 seconds, a unique open-source "emotion exaggeration" control — plus a built-in neural watermark, a welcome ethical touch. Qwen3-TTS, released in January 2026, is technically the most complete (3-second cloning, natural-language voice design, streaming, MLX ports for Apple Silicon) with only six months of community track record. Kokoro remains the fascinating outsider: 82M parameters, faster than real time on CPU — perfect for a lean automated pipeline, as long as the single French voice is enough.
Paid: 1. ElevenLabs v3 (quality reference) · 2. OpenAI gpt-4o-mini-tts (~7× cheaper) · 3. Cartesia Sonic-3.5 (real time). Open source, local: 1. Chatterbox Multilingual V3 (MIT + FR + cloning) · 2. Qwen3-TTS 1.7B (most complete) · 3. Kokoro-82M (tiny, real time on CPU).
Local LLMs: what to run under 36 GB
Let's set expectations first: the open-weights stars of 2026 (DeepSeek V4, GLM-5.2, Kimi K2.6) weigh 300 to 750 billion parameters — out of budget for a personal machine. Under 36 GB of memory (unified RAM or GPU VRAM), the competition happens between 20–35B models, with a simple trade-off: MoE models (few active parameters) favour speed, dense ones favour raw quality. Mind the Mistral Small 4 trap: despite the name it's a 119B MoE — about 60 GB at 4-bit, it does not fit.
| Model | Params (active) | Q4 ≈ | Indicative speed | Strength |
|---|---|---|---|---|
| Qwen3.6-35B-A3B | 35B (3B) | 22 GB (Q6: 29 GB) | 35–50 tok/s, up to ~112 with MLX | the generalist: quality + speed + 262K context |
| Qwen3.6-27B (dense) | 27B | 17 GB (Q8 possible) | 10–25 tok/s | quality ceiling: SWE-bench 77.2*, GPQA-D 87.8* |
| Gemma 4 31B | 31B | 20 GB | 8–25 tok/s (×3 with MTP) | 140+ languages, vision, now Apache 2.0 |
| gpt-oss-20b | 21B (3.6B) | 12 GB | 150–170 tok/s | speed and tool use; collapses at 128K context |
| Magistral Small 1.2 | 24B | 14–15 GB | ~20 tok/s | reasoning + vision + very good French |
* Self-reported by Alibaba — the "a dense 27B beats a 397B MoE at coding" claim has no solid independent verification yet.
On the runtime side, 2026 reshuffled the deck: Ollama now uses MLX as its backend on Apple Silicon (since 0.19, March 2026), and both LM Studio and llama.cpp shipped MTP speculative decoding — up to three times faster on Gemma 4.
# Ollama ≥ 0.19 (MLX backend on Apple Silicon)
# Pulling straight from Hugging Face avoids guessing tags:
ollama run hf.co/unsloth/Qwen3.6-35B-A3B-GGUF:Q4_K_M # ~22 GB — the generalist
ollama run gpt-oss:20b # ~12 GB — 150+ tok/s, agentsCompared with 24 GB setups, you don't just gain "a bigger model": you can serve 20–27B models at Q6/Q8 instead of Q4 — higher quantization quality on the same model, often a better deal than a bigger model poorly quantized.
- Qwen3.6-35B-A3B — the default pick: Apache 2.0, fast (MoE), 262K context.
- Qwen3.6-27B — maximum quality for code and reasoning, when latency isn't critical.
- Gemma 4 31B — the multilingual/multimodal pick: 140+ languages (excellent French), vision, MTP.
Mentions: gpt-oss-20b as an ultra-fast agent engine; Magistral Small 1.2 for French-language reasoning with vision.
The top 10 LLMs, all categories — July 2026
The first half of 2026 was uniquely dense: five flagship models from Anthropic in six months, six weeks between GPT-5.4 and GPT-5.5, and Chinese open-weights joining the frontier on code. Composite ranking (Artificial Analysis Intelligence Index, June 2026, plus Arena and SWE-bench Verified/Pro):
| # | Model | Vendor | Licence | Context | API price ($/M in/out) | Signature |
|---|---|---|---|---|---|---|
| 1 | Claude Fable 5 / Mythos 5 | Anthropic | proprietary | 1M | 10 / 50 | AAII 64.9 (record); SWE-bench 95% |
| 2 | Claude Opus 4.8 | Anthropic | proprietary | 1M | 5 / 25 | #1 Arena; best frontier reliability/price ratio |
| 3 | GPT-5.5 | OpenAI | proprietary | 1M | 5 / 30 (Pro: 30 / 180) | competition math, agents |
| 4 | Gemini 3.1 Pro | proprietary | 1M | 2 / 12 | GPQA Diamond 94.3%; factuality | |
| 5 | Qwen 3.7 Max | Alibaba | proprietary (API) | 1M | 2.50 / 7.50 | best intelligence-per-dollar |
| 6 | DeepSeek V4 | DeepSeek | open weights (MIT) | 1M | 0.44 / 0.87 | SWE-bench 80.6% at ~5% of closed-model prices |
| 7 | GLM-5.2 | Zhipu AI | open weights (MIT) | 1M | — | #1 SWE-bench Pro (62.1)* |
| 8 | Kimi K2.6 | Moonshot | open weights | 256K | 0.60 / 2.50 | tool-assisted HLE 54%; agents |
| 9 | MiniMax M3 | MiniMax | open weights announced* | 1M | ~5–10% of GPT-5.5 | low-cost multi-actor agents |
| 10 | Grok 4.3 | xAI | proprietary | 256K | ~1.25 / 2.50 | cheap real-time agents |
* GLM-5.2 and MiniMax M3 scores are self-reported, without consolidated independent verification in early July; the actual publication of M3's weights was still to be confirmed. (And yes, in full transparency: the #1 model in this table helped write this article — the numbers come from independent leaderboards, not from us.)
Four underlying trends sum up the semester. One: the frontier is now decided on agentic benchmarks (SWE-bench Pro, Terminal-Bench 2.1, GDPval) — GPQA is saturated above 94%. Two: prices have forked — "GPT-4-class" now costs under $1/M tokens while the frontier premium climbs (GPT-5.5 Pro at 30/180). Three: frontier open-weights are almost exclusively Chinese (DeepSeek, Zhipu, Moonshot, MiniMax, Qwen) — to the point that the US NIST officially evaluates them; Meta pivoted to proprietary (Muse Spark) and Mistral remains the only Western open flagship. Four: 1M context is now the top-10 standard — only Kimi stays at 256K.
The recap card — the state of the art on one page
| Need | The pick | The alternative | The open option |
|---|---|---|---|
| Edit a video | DaVinci Resolve Studio 21 ($295 for life) | CapCut Pro (short-form) · Descript (podcast) | Resolve free edition |
| Generate slides | Gamma | Plus AI (enterprise .pptx) | Presenton (Apache 2.0) |
| Cloud voice-over | ElevenLabs v3 | OpenAI gpt-4o-mini-tts (budget) · Cartesia (real time) | — |
| Local voice-over | Chatterbox Multilingual V3 (MIT) | Qwen3-TTS 1.7B | Kokoro-82M (real time on CPU) |
| Local LLM ≤ 36 GB | Qwen3.6-35B-A3B | Qwen3.6-27B (quality) · Gemma 4 31B (FR, vision) | all Apache 2.0 |
| Frontier LLM (API) | Claude Fable 5 · Opus 4.8 (perf/price) | GPT-5.5 · Gemini 3.1 Pro | DeepSeek V4 (MIT) |
Three reflexes before pulling out the credit card: read the licence of the weights (not the code), convert "credits" into real cost at your monthly volume, and always export your content to an open format — Tome reminded everyone in 2025 that SaaS products die too.